Systems and methods for characterizing a biological condition or agent using selected gene expression profiles

ABSTRACT

Methods are provided for evaluating a biological condition of a subject using a calibrated profile data set derived from a data set having a plurality of members, each member being a quantitative measure of the amount of a subject&#39;s RNA or protein as distinct constituents in a panel of constituents. The biological condition may be a naturally occurring physiological state or may be responsive to treatment of the subject with one or more agents. Calibrated profile data sets may be used as a descriptive record for an agent.

RELATED APPLICATIONS

[0001] This application is a divisional of U.S. application Ser. No.09/821,850, filed Mar. 29, 2001, which is a continuation in part of U.S.application Ser. No. 09/605,581, filed Jun. 28, 2000, which applicationclaims priority from provisional application Ser. No. 60/141,542, filedJun. 28, 1999 and provisional application Ser. No. 60/195,522 filed Apr.7, 2000. These related applications are hereby incorporated herein byreference.

TECHNICAL FIELD

[0002] Embodiments of the recent invention provide systems and methodsutilizing gene expression analysis for characterizing a biologicalcondition or agent.

BACKGROUND ART

[0003] There has been substantial discussion including congressionalhearings concerning medical errors. One source of medical errorsincludes errors with medications. Upwards of 98,000 hospitalizedpatients annually have been documented to be victims of medicationerrors (Statement of the American Pharmaceutical Association to theSenate Appropriations Committee Labor, health and Human ServicesEducation Subcommittee Hearing on Medical Errors Dec. 13, 1999). Theseerrors include problems arising from drug interactions for a particularpatient taking more than one drug, problems concerning the response ofan individual to a particular drug and incorrect medication for aparticular condition. Medical errors further arise as a result ofmisdiagnosis. This may occur as a result of insensitive diagnostictechniques or a wide range of interpersonal variability in the manner inwhich a clinical state is manifest. At present, there are few toolsavailable for optimizing prognosis, diagnosis and treatment of a medicalcondition taking into account the particular phenotype and genotype ofan individual.

[0004] There has been increasing interest in herbal drugs ornutraceuticals. These compounds are grown and collected from around theworld, and consequently the compounds are subject to regional andtemporal differences in collection and preparation that are difficult tocontrol. It is frequently the case that one batch of a nutraceutical maybe effective, there is no assurance that a second batch will beeffective. Moreover, analysis of nutraceuticals is problematic becausethese drugs are complex mixtures in which little is known with respectto the active agent.

[0005] All new therapeutic agents require some form of clinical trials.It is known that a drug for treating tumor that is tested in a clinicaltrial using standard recruiting techniques for patients, may in factshow only limited efficacy. If the beneficial effect observed in aclinical population is too small, the drug will not receive approval bythe Food and Drug Administration for use in the population at large.However, the small beneficial effect observed may in fact be an artifactof the clinical trial design or the clinical endpoint in the populationof patients. It would be desirable to have criteria for screeningpatients as they enter a clinical trial to ensure that the beneficialeffect of a drug if it exists may be detected and quantified.

SUMMARY OF THE INVENTION

[0006] In a first embodiment of the invention there is provided amethod, for evaluating a biological condition of a subject, thatincludes: obtaining from the subject a sample having at least one ofRNAs and proteins; deriving from the sample a first profile data set,the first profile data set including a plurality of members, each memberbeing a quantitative measure of the amount of a distinct RNA or proteinconstituent in a panel of constituents selected so that measurement ofthe constituents enables measurement of the biological condition; andproducing a calibrated profile data set for the panel, wherein eachmember of the calibrated profile data set is a function of acorresponding member of the first profile data set and a correspondingmember of a baseline profile data set for the panel, the calibratedprofile data set providing a measure of the biological condition of thesubject.

[0007] In another embodiment, a method is provided for evaluating abiological condition of a subject, that includes obtaining from thesubject a first sample having at least one of fluid, cells and activeagents; applying the first sample or a portion thereof to a definedpopulation of indicator cells; obtaining from the indicator cells asecond sample containing at least one of RNAs or proteins; deriving fromthe second sample a first profile data set, the first profile data setincluding a plurality of members, each member being a quantitativemeasure of the amount of a distinct RNA or protein constituent in apanel of constituents selected so that measurement of the constituentsenables measurement of the biological condition; and producing acalibrated profile data set for the panel, wherein each member of thecalibrated profile data set is a function of a corresponding member ofthe first profile data set and a corresponding member of a baselineprofile data set for the panel, the calibrated profile data setproviding a measure of the biological condition of the subject.

[0008] In a another embodiment, a method is provided for evaluating abiological condition affected by an agent, the method including:obtaining, from a target population of cells to which the agent has beenadministered, a sample having at least one of RNAs and proteins;deriving from the sample a first profile data set, the first profiledata set including a plurality of members, each member being aquantitative measure of the amount of a distinct RNA or proteinconstituent in a panel of constituents selected so that measurement ofthe constituents enables measurement of the biological condition; andproducing a calibrated profile data set for the panel, wherein eachmember of the calibrated profile data set is a function of acorresponding member of the first profile data set and a correspondingmember of a baseline profile data set for the panel, the calibratedprofile data set providing a measure of the biological condition asaffected by the agent.

[0009] In a another embodiment, a method is provided for evaluating theeffect on a biological condition by a first agent in relation to theeffect by a second agent, including: obtaining, from first and secondtarget populations of cells to which the first and second agents havebeen respectively administered, first and second samples respectively,each sample having at least one of RNAs and proteins; deriving from thefirst sample a first profile data set and from the second sample asecond profile data set, the profile data sets each including aplurality of members, each member being a quantitative measure of theamount of a distinct RNA or protein constituent in a panel ofconstituents selected so that measurement of the constituents enablesmeasurement of the biological condition; and producing for the panel afirst calibrated profile data set and a second profile data set, wherein(i) each member of the first calibrated profile data set is a functionof a corresponding member of the first profile data set and acorresponding member of a first baseline profile data set for the panel,and (ii) each member of the second calibrated profile data set is afunction of a corresponding member of the second profile data set and acorresponding member of a second baseline profile data set for thepanel, the calibrated profile data sets providing a measure of theeffect by the first agent on the biological condition in relation to theeffect by the second agent.

[0010] In a further embodiment, a method of conducting a clinical trialof an agent, is provided, including: causing the blind administration ofa selected one of a placebo and the agent to each candidate of a pool ofsubjects; and using quantitative gene expression to monitor an effect ofsuch administration.

[0011] In another embodiment, a digital storage medium is provided onwhich is stored a computer readable calibrated profile data set,wherein: the calibrated profile data set relates to a sample having atleast one of RNAs and proteins derived from a target cell population towhich an agent has been administered; the calibrated profile data setincludes a first plurality of members, each member being a quantitativemeasure of a change in an amount of a distinct RNA or proteinconstituent in a panel of constituents selected so that measurement ofthe constituents enables measurement of a biological condition asaffected by administration of the agent.

[0012] In another embodiment, a digital storage medium is provided onwhich is stored a plurality of records R_(i) relating to a population ofsubjects, each record R_(i) corresponding to a distinct instance P_(i)of a computer readable profile data set P wherein: each instance P_(i)of the profile data set P relates to a distinct sample derived from asubject, the sample having at least one of RNAs and proteins; theprofile data P set includes a plurality of members M_(j), each memberM_(j) being a quantitative measure of the amount of a distinct RNA orprotein constituent in a panel of constituents selected so thatmeasurement of the constituents enables measurement of a biologicalcondition; each record R_(i) includes, for each member M_(ij) of acorresponding distinct instance P_(i) of the profile data set P, a valuecorresponding to the value of the member M_(ij); and each record R_(i)also includes a reference to a characteristic of the subject relative tothe record, the characteristic being at least one of age group, gender,ethnicity, geographic location, diet, medical disorder, clinicalindicator, medication, physical activity, body mass, and environmentalexposure.

[0013] In a further embodiment, a digital storage medium is provided onwhich is stored a large number of computer readable profile data sets,wherein each profile data set relates to a sample derived from a targetcell population to which has been administered an agent, the samplehaving at least one of RNAs and proteins; each profile data set includesa plurality of members, each member being a quantitative measure of theamount of a distinct RNA or protein constituent in a panel ofconstituents selected so that measurement of the constituents enablesmeasurement of a biological condition; and the panel is the same for allprofile data sets.

[0014] In a another embodiment of the invention, a method is providedfor evaluating a biological condition of a subject, based on a samplefrom the subject, the sample having at least one of RNAs and proteins,the method including: deriving from the sample a first instance of aprofile data set, the profile data set including a plurality of members,each member being a quantitative measure of the amount of a distinct RNAor protein constituent in a panel of constituents selected so thatmeasurement of the constituents enables measurement of the biologicalcondition; and producing a first instance of a calibrated profile dataset for the panel, wherein each member of an instance of the calibratedprofile data set is a function of a corresponding member of an instanceof the profile data set and a corresponding member of an instance of abaseline profile data set for the panel, the calibrated profile data setproviding a measure of the biological condition of the subject;accessing data in a condition database, the condition database having aplurality of records relating to a population of subjects, each recordcorresponding to a distinct instance of the calibrated profile data set;and evaluating the first instance of the calibrated profile data set inrelation to data in the condition database.

[0015] In another embodiment of the invention, a method is provided ofdisplaying quantitative gene expression analysis data associated withmeasurement of a biological condition, the method including: identifyinga first profile data set pertinent to the gene expression analysis data,the first profile data set including a plurality of members, each memberbeing a quantitative measure of the amount of a distinct RNA or proteinconstituent in a panel of constituents selected so that measurement ofthe constituents enables measurement of the biological condition;producing a calibrated profile data set for the panel, wherein eachmember of the calibrated profile data set is a function of acorresponding member of the first profile data set and a correspondingmember of a baseline profile data set for the panel, the calibratedprofile data set providing a measure of the biological condition of thesubject; and displaying the calibrated profile data set in a graphicalformat.

[0016] Another embodiment is directed to a descriptive record of achange in a biological condition, that includes: a first set ofnumerical gene expression values for a panel of gene loci, each value inthe set corresponding to a single gene locus in a panel of gene loci,the set of values forming a profile data set for a population of cellssubjected to a first biological condition; a second set of numericalgene expression values for the panel of gene loci, each value in the setcorresponding to a single gene locus, the set of values forming abaseline profile data set for a second population of cells subjected toa second biological condition, the second set of values optionally beingan average for multiple gene expression values from multiple populationsof cells for each locus in the panel; and a third set of numberscorresponding to the ratio of the first set of values and the second setof values with respect to each gene locus in the panel, the third setbeing a calibrated profile data set; the profile data set and thecalibrated profile data set being descriptive of the first biologicalcondition with respect to the second biological condition.

[0017] In another embodiment, a method for diagnosing a biologicalcondition of a subject is provided that includes: obtaining a samplefrom a subject; subjecting a population of cells to the sample anddetermining the presence of a first biological condition with respect toa second biological condition according to any of the above claims.

[0018] In another embodiment, a method is provided for diagnosing asusceptibility for a biological condition in a subject, that includesobtaining a sample from the subject; creating a descriptive record,according to the above, wherein the baseline set of values is an averageof second values contained in a library of descriptive records for thesecond biological condition; the library containing a plurality ofdescriptive records grouped according to a predetermined biologicalcondition; comparing the calibrated profile data set of the subject withthe library of calibrated profile data sets and diagnosing thesusceptibility of the subject.

[0019] In another embodiment, a method is provided for monitoring theprogress of a biological condition, including: creating a plurality ofdescriptive records, according to the above; wherein each set of firstvalues is determined at preselected time intervals with respect to thefirst record; comparing each calibrated profile data set with a libraryof calibrated profile data sets, the plurality of calibrated profiledata sets being grouped according to a predetermined biologicalcondition; and determining the progress of the biological condition withrespect to gene expression.

[0020] In another embodiment, a method is provided for establishing thebiological activity of a composition, including: selecting a populationof cells; subjecting the cells to the composition; and determining therecord according to the above description using a standardized baselineprofile data set for the biological condition.

[0021] In another embodiment, a method is provided for determining whichtherapeutic agent from a choice of a plurality of therapeutic agents toadminister to a subject so as to change a biological condition in asubject from a first biological condition to a second biologicalcondition; including: subjecting a sample from the subject to each of aplurality of therapeutic agents; determining a descriptive record foreach of the samples according to any of the above described methods,comparing each of the calibrated profile data sets to a library ofcalibrated profile data sets, the library of calibrated data sets beinggrouped according to a predetermined biological condition; anddetermining which of the therapeutic agents is capable of changing thefirst biological condition in the subject to the second biologicalcondition in the subject.

[0022] In another embodiment, a method is provided for characterizingthe biological effectiveness of a single batch of a composition producedby a manufacturing process, comprising: providing a fingerprint orsignature profile according to any of the above methods; and labelingthe batch of the composition by placing the fingerprint (signatureprofile) on each container in the batch.

[0023] In another embodiment, a method is provided for accessingbiological information on a digital storage medium as described above,including: making the information available to a user.

[0024] In another embodiment, a method is provided for consumerevaluation of a product, wherein the consumer evaluation is dependent ona signature profile, including: identifying the product using thesignature profile.

[0025] In another embodiment, a computer program product is provided forevaluating a biological condition of a subject or for evaluating abiological condition resulting from the use of an agent, including acomputer usable medium having computer readable program code thereon,the computer program code; including: a program code for classifying asample from the subject or the agent for an identifiable record; aprogram code for deriving a first data set, the first profile data setincluding a plurality of members, each member being a quantitativemeasure of the amount of a distinct RNA or protein constituent in apanel of constituents selected so that measurement of the constituentsenables measurement of the biological condition; the profile data setbeing stored in the record; and a program code for optionally producinga calibrated profile data set for the panel, for storage in the record,each member of the calibrated profile data set being a function of acorresponding member of the first profile data set and a correspondingmember of a baseline profile data set for the panel, the calibratedprofile data set providing a measure of the biological condition of thesubject.

[0026] In another embodiment of the invention, a computer system forevaluating a biological condition of a subject or for evaluating abiological condition resulting from the use of an agent is provided, thecomputer system, including: a classification module for classifying asample from the subject or the agent in an identifiable record; aderivative module for deriving a first data set, the first profile dataset including a plurality of members, each member being a quantitativemeasure of the amount of a distinct RNA or protein constituent in apanel of constituents selected so that measurement of the constituentsenables measurement of the biological condition; and a production modulefor producing a calibrated profile data set for the panel, wherein eachmember of the calibrated profile data set is a function of acorresponding member of the first profile data set and a correspondingmember of a baseline profile data set for the panel, the calibratedprofile data set providing a measure of the biological condition of thesubject.

[0027] In another embodiment, a method is provided for analyzing apatient for a biological condition at a remote site, including:providing a kit for measuring a profile data base for evaluating abiological condition, the kit including reagents for quantitativeanalysis of RNA or protein for a panel of gene loci; accessing acentralized database containing baseline profile data sets correspondingto the panel; determining the calibrated profile data set for thepatient; and analyzing the biological condition of the patient.

[0028] Further embodiments of the invention include the use ofcalibrated profile data bases for determining the biological conditionat one site in a subject from a sample taken from a second remote site.The biological condition may include disease, therapeutic interventions,aging, health conditioning and exercise, exposure to toxins, status ofinfection and health status. For example, calibrated precision profilesmay be used to measure a biological condition(s) in one site (forexample, the liver) by sampling cells from the same subject, but at adifferent site not generally considered a target for the biologicalcondition, for example, peripheral blood cells in the case of liverdisease.

[0029] Further embodiments of the invention include the use ofcalibrated profile data bases for determining the biological conditionof the subject that includes placing a cell or fluid sample on indicatorcells to assess the biological condition, the biological conditionincluding disease, therapeutic interventions, aging, health conditioningand exercise, exposure to toxins, status of infection and health status.

[0030] Further embodiments of the invention include the use ofcalibrated profile data bases and profiles to assess, compare andcontrast the bioactivities of therapeutic agents and therapeutic agentcandidates including comparison of two agents having unknown properties;comparison of agents that are complex mixtures against those that aresimple mixtures and comparisons of a single agent against a class ofagents.

[0031] Further embodiments of the invention include the use ofcalibrated profile databases derived from in vitro dosing of an agent inindicator cells, or fluids or cells ex vivo to predict in vivoactivities, activities including efficacy and toxicity and furtherpermitting data on short term in vivo dosing of agent to predictlong-term activities as described herein.

[0032] Another embodiment of the invention is at least one databases andits uses, the databases containing at least one of calibrated profiledata sets and baseline profile data sets for discrete populationsidentified according to factors including diseases, geography,ethnicity, age and state of health.

[0033] A further embodiment of the invention is a database correspondingto an individual over time, the uses including managing a personalizedhealth care program.

[0034] Additional embodiments include methods of running a clinicaltrial using calibrated profile data and databases containing calibratedprofile data from in vitro and in vivo studies of the effect of theagent on populations of cells and methods of building a clinicalresearch network that uses calibrated profile data and traditionalmedical data.

[0035] Another embodiment of the invention provides a method, forevaluating a biological condition of a subject. This method includes:

[0036] a. obtaining from the subject a sample having at least one ofRNAs and proteins;

[0037] b. deriving from the sample a first profile data set, the firstprofile dataset including a plurality of members, each member being aquantitative measure of the amount of a distinct RNA or proteinconstituent in a panel of constituents selected so that measurement ofthe constituents enables measurement of the biological condition; and

[0038] c. producing a calibrated profile data set for the panel, whereineach member of the calibrated profile data set is a function of acorresponding member of the first profile data set and a correspondingmember of a baseline profile data set for the panel, the calibratedprofile data set providing a measure of the biological condition of thesubject.

[0039] In this embodiment, the biological condition relates toinflammation and the panel includes at least half, and, optionally, atleast eighty percent of the constituents of the Inflammation SelectedPanel of Table 1. In a related embodiment, the biological conditionrelates to cell growth and differentiation and the panel includes atleast half, and optionally at least eighty percent, of the constituentsof the Cell Growth and Differentiation Selected Panel of Table 2. Inother related embodiments, the biological condition relates tometabolism and toxicity and the panel includes at least half, andoptionally at least eighty percent, of the constituents of the LiverMetabolism and Toxicity Selected Panel of Tables 3 or 7. In anotherrelated embodiment, the biological condition relates to skin responseand the panel includes at least half, and optionally at least eightypercent, of the constituents of the Skin Response Selected Panel ofTable 4. In another related embodiment, the biological condition relatesto the vascular system and the panel includes at least half, andoptionally, at least eighty percent, of the constituents of the VascularSelected Panel of Table 6. In a further related embodiment, thebiological condition relates to the prostate health and disease and thepanel includes at least half, and optionally at least eighty percent ofthe constituents of the Prostate Selected Panel of Table 5.

[0040] Another embodiment of the invention provides a method, forevaluating a biological condition of a subject, that includes: obtainingfrom the subject a sample having at least one of RNAs and proteins;deriving from the sample a profile data set, the profile data setincluding a plurality of members, each member being a quantitativemeasure of the amount of a distinct RNA or protein constituent in apanel of constituents selected so that measurement of the constituentsenables measurement of the biological condition; wherein suchmeasurement is performed for each constituent under conditions whereinefficiencies of amplification for all constituents are substantiallysimilar, the profile data set providing a measure of the biologicalcondition of the subject.

[0041] Another embodiment of the invention provides a method, forevaluating a biological condition of a subject, that includes: obtainingfrom the subject a first sample having at least one of fluid, cells andactive agents; applying the first sample or a portion thereof to adefined population of indicator cells; obtaining from the indicatorcells a second sample containing at least one of RNAs or proteins;deriving from the second sample a profile data set, the profile data setincluding a plurality of members, each member being a quantitativemeasure of the amount of a distinct RNA or protein constituent in apanel of constituents selected so that measurement of the constituentsenables measurement of the biological condition; wherein such measure isperformed for each constituent under conditions wherein efficiencies ofamplification for all constituents are substantially similar, theprofile data set providing a measure of the biological condition of thesubject.

[0042] Another embodiment of the invention provides method forevaluating a biological condition affected by an agent, the method thatincludes obtaining, from a target population of cells to which the agenthas been administered, a sample having at least one of RNAs andproteins; deriving from the sample a profile data set, the profile dataset including a plurality of members, each member being a quantitativemeasure of the amount of a distinct RNA or protein constituent in apanel of constituents selected so that measurement of the constituentsenables measurement of the biological condition; wherein such measure isperformed for each constituent under conditions wherein efficiencies ofamplification for all constituents are substantially similar, theprofile data set providing a measure of the biological condition asaffected by the agent.

[0043] Efficiencies of amplification of all constituents may differ byless than approximately 2%. The efficiencies of amplification may differby less than approximately 1%. Moreover, in any of the embodiments ofthe invention described above which refers to a panel, the panel mayinclude at least four constituents selected from any one of Tables 1through 7. For example, at least four constituents may be selected fromthe group consisting of expression products of TNF-α, IL-1-α, IL-β,IFN-γ, IL-8, and IL-10.

[0044] In another embodiment of the invention, a kit is provided havingprimer-probe combinations for measuring expression products of at leastfour constituents selected from any one of Tables 1 through 7. The kitmay further include a primer probe combination constructed so as tohybridize only to at least one of cDNA and mRNA at a biologicallyrelevant locus. Moreover, in each combination, a reverse primer may beselected which is complementary to a coding DNA strand located across anintron-exon junction, with not more than three bases of a three-primeend of the reverse primer being complementary to a proximal exon.

BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The foregoing features of the invention will be more readilyunderstood by reference to the following detailed description, takenwith reference to the accompanying drawings, in which:

[0046]FIG. 1 is a diagram showing the flow of information from dataacquired in molecular pharmacology and toxicology, clinical testing, anduse of the data for the application to individualized medicine.

[0047]FIG. 2 is a diagram showing the drug discovery pathway of newcompounds from early leads to likely drug candidates. Althoughcalibrated profile data sets are indicated at the pre-clinical step,gene expression data can be acquired and is useful at any of the stagesshown. IND refers to investigative new drug and refers to an early stagein regulatory review.

[0048]FIG. 3 is a diagram presenting a comparison of in vivo and invitro protocols for forming calibrated profile data sets for rapidlyassessing product candidate toxicity and efficacy in accordance withseveral embodiments of the present invention.

[0049]FIG. 4 is a diagram showing the application of gene expressionprofiling as a guide to pre-clinical and clinical studies in accordancewith an embodiment of the present invention.

[0050]FIG. 5 is a diagram showing a method in accordance with anembodiment of the present invention for obtaining profile data in theabsence of a stimulus and in the presence of a stimulus.

[0051]FIG. 6 is a diagram showing the creation of a library of profiledata associated with a plurality of subjects in accordance with anembodiment of the present invention.

[0052]FIG. 7 is a diagram illustrating the structure of a profile datarecord in accordance with an embodiment of the present invention.

[0053]FIG. 8 is a diagram illustrating a data entry screen for a datarecord of the type shown in FIG. 7 and typical contexts in which datarecords may be compiled in accordance with embodiments of the presentinvention.

[0054]FIG. 9 shows an embodiment of the present invention in whichprofile data, in either the raw or calibrated form, is evaluated usingdata from a database that is remotely accessed over a network.

[0055]FIG. 10 shows a schematic of a phase two clinical trial thatutilizes gene expression profiling (a). The right hand panel (b)indicates that the same information may be used in Phase IV or postmarketing studies to compare the efficacy of already approved andmarketed drugs or to guide the marketing of such therapies; to guide thechoice of therapy for an individual subject or population from within aclass of appropriate compounds.

[0056]FIG. 11 is a bar graph that shows a graphical representation inthe form of a histogram representing calibrated profile data sets basedon quantitative expression of RNA in cells of a whole blood sample usinga panel of 12 constituents where each constituent corresponds to aunique gene locus. (a) The blood sample is stimulated ex vivo with heatkilled staphylococci are further exposed H7-TPCK, H9-UT-77, or H16-Dexas indicated. The baseline profile data set is a blood sample stimulatedex vivo (in vitro) with heat killed staphylococci (b) The blood sampleis stimulated ex vivo with lipopolysaccharide (LPS) and is then furtherexposed to compounds H7-TPCK, H9-UT-77, or H16-Dex as indicated.

[0057]FIG. 12 is a bar graph with a logarithmic axis that shows agraphical representation of calibrated profile data sets for whole bloodstimulated ex vivo with lipopolysaccharide (LPS), using a panel of 9constituents, each constituent corresponding to a gene locus encodingthe gene products indicated, the blood being further exposed toanti-inflammatory agents: methotrexate, meclofenamate andmethylprednisolone. The baseline profile data set is derived from LPSstimulated (but otherwise untreated) cells.

[0058]FIG. 13 are bar graphs with a logarithmic axis that shows agraphical representation of calibrated profile data sets for twodifferent samples of whole blood (a) 991116 and (b) 991028 reflectingthe biological condition of the cells using a panel of 24 members, eachmember corresponding to a gene locus, the baseline profile data setbeing derived from untreated cells. The calibrated data sets for cellsexposed for six hours to three inflammation inducing agents(lipopolysaccharide, heat killed staphylococci, and phytohemagglutinin)are compared for each sample. (c) shows a direct comparison of LPSstimulated 991116 with respect to 991028 as the baseline profile dataset (d) shows a direct comparison between unstipulated 991116 and991028.

[0059]FIG. 14 is a bar graph with a logarithmic axis that shows agraphical representation of calibrated profile data sets using a panelof 22 constituents, each constituent corresponding to a gene locus, thebaseline profile data set being derived from untreated cells. Wholeblood is exposed for six hours ex vivo to three inflammation inducingagents (lipopolysaccharide, heat killed staphylococci, andphytohemagglutinin) which are then treated with a singleanti-inflammatory agent (methyl prednisolone) to reveal similarities anddifferences in the effect of a single agent on cell populationsdiffering in their biological condition.

[0060]FIG. 15 is a bar graph with a logarithmic axis that shows agraphical representation of calibrated profile data sets for whole bloodwhere one calibrated data set refers to a subject (subject 2) who hasbeen treated in vivo with a corticosteroid (dexamethasone), a seconddata set refers to the treatment of a blood sample from the same subjectprior to in vivo treatment where that sample has been treated ex vivo(in vitro) and the third data set refers to a second subject treated invivo with dexamethasone (subject 1). The data sets demonstrate thereproducibility and predictability of an ex vivo (in vitro) treatment ofblood compared to in vivo treatment with the same agent. The figure alsoshows minor variation between samples from different subjects reflectinginterpersonal variability. A panel of 14 constituents is provided. Thebaseline profile data set is derived from untreated whole blood from thecognate subject.

[0061]FIG. 16 is a bar graph with a logarithmic y axis that shows agraphical representation of calibrated profile data sets for whole bloodwhere one calibrated data set refers to (a) 2 subjects who have beentreated in vivo with an inactive placebo for 3 days and (b) activeprednisolone for 3 days at 100 mg/day. The data set shows some variationbetween samples from different subjects treated with the same drug. Thedata sets demonstrate similarity of responses across the same gene loci,as well as, quantitative variation at other loci suggesting quantifiableinterpersonal variation. A panel of eight members is provided. Thebaseline profile data set is derived from untreated whole blood.

[0062]FIG. 17 is a bar graph with logarithmic y axis that shows agraphical representation of calibrated selected profile data sets fortwo samples taken from a single subject within a 19 day period using apanel (e.g., inflammation panel) of 24 members where each membercorresponds to a unique gene locus. The baseline profile data setrelates to peripheral blood taken from the subject prior to treatment.

[0063] FIGS. 18(a) through 18(e) are bar graphs with a logarithmic axisthat show a graphical representation of calibrated profile data sets foreach of 5 subjects from which a blood sample has been taken. Each of theblood samples was exposed to the inflammatory agent phytohemagglutinin(PHA) or to a therapeutic agent (anti-inflammatory agent) at differentconcentrations: 0.1 μM, 0.3 μM, 1 μM, 3 μM and 5 μM, for a 4 hour periodex vivo (in vitro) so as to determine the optimum dose for treating thesubject. A panel of 6 constituents was used corresponding to 6 geneloci. The baseline profile data set was an untreated sample obtainedfrom the cognate donor.

[0064]FIG. 19 is a bar graph with a logarithmic axis that shows agraphical representation of calibrated profile data sets for threedifferent subjects having different biological conditions using a panelwith 24 constituents. The profile data sets show variability accordingto these conditions providing the basis for a diagnostic signaturepanel: (a) shows a calibrated profile data set for a smoker against abaseline for a non-smoker. (b) shows a calibrated profile data set for asubject with chronic obstructive pulmonary disease against a baselinefor a subject lacking this disease. The baseline profile data set isderived from a subject that is “normal” with respect to theseconditions.

[0065]FIG. 20 illustrates that an individual responses can bedistinguished from a similarly treated population. A comparison of theresponse of a single animal compared to its experimental cohort (n=5animals) with respect to a single locus (GST-P) is provided. Thebaseline data set is the cohort average. The figures shows that thisanimal varied significantly from the daily, population average in thefirst two days of the study, but became more similar to the cohortaverage with time after treatment with acetaminophen.

[0066]FIG. 21 is a bar graph with a logarithmic axis that shows agraphical representation of calibrated profile data sets for samples ofblood treated ex vivo with LPS or LPS and one of three anti-inflammatoryherbals (Echinacea, Arnica or Siberian Ginseng) at a concentration of200 μg/ml. A panel of 24 constituents is used. The baseline profile dataset is derived from LPS stimulated cells absent a herbal treatment. Thefigure illustrates the effectiveness of the use of the calibratedselected profile to investigate the overall effects of complex compoundssuch as nutraceuticals whose biological effect is a summation of morethan one activity. In this case, each of the herbals is consumed as animmunostimulant, however the calibrated selected profiles reveal aunique pattern shows a mixture of both immunostimulatory andanti-inflammatory effects.

[0067]FIG. 22 is a bar graph with a logarithmic axis that shows agraphical representation of calibrated profile data sets for samples ofblood treated ex vivo with LPS or LPS and methylprednisolone or LPS andArnica. The baseline profile data set is LPS treated blood sample.

[0068]FIG. 23 is a bar graph with a logarithmic axis that shows agraphical representation of calibrated profile data sets for samples ofTHP-1 cells treated with LPS or LPS and Arnica at three differentconcentrations using a panel of 22 constituents. The baseline profiledata set is untreated THP-1 cells. The figure illustrates aconcentration response with respect to the gene expression across thecalibrated profile.

[0069]FIG. 24 is a bar graph with a logarithmic axis that shows agraphical representation of calibrated profile data sets for samples ofTHP-1 cells treated ex vivo with four different commercial brands ofEchinacea using a panel of 8 constituents. The baseline profile data setis untreated THP-1 cells.

[0070]FIG. 25 illustrates the use of the calibrated profile to comparerelative efficacy across brands, or different formulations. Calibratedprofile data sets for herbal preparations from different manufacturingsources with respect to an indicator monocytic cell line (THP-1) areshown graphically, the baseline profile data set being THP-1 cellsabsent the herbal. (a) Three commercial herbal Echinacea preparations at250 (μg/ml); (b) three herbal preparations at different concentrations(250 μg/ml, 50 μg/ml and 3-10 μg/ml) (c) four commercial Echinaceabrands at 250 μg/ml).

[0071] FIGS. 26(a) through 26(d) illustrate calibrated profile datasets, using a subset of the Inflammation Selected Panel, that show theeffect of administration of a steroid.

[0072] FIGS. 27(a) through 27(d) illustrate calibrated profile datasets, using a subset of the Inflammation Selected Panel, providing acomparison of the effects of administration of methylprednisolone andIbuprofen.

[0073] FIGS. 28(a) through 28(d) illustrate calibrated profile datasets, using a subset of the Inflammation Selected Panel, in identifyingchronic obstructive pulmonary disease (COPD) patients.

[0074] FIGS. 29(a) and 29(b) provide illustrations in which evaluationsof the effects of drug exposure performed in vitro correspond closelywith evaluations performed in vivo, employing in each case calibratedprofile data sets, using a subset of the Inflammation Selected Panel.

[0075]FIG. 30 illustrates the effect of different agents evaluated usinga subset of the Selected Prostate Panel, and shows broad functions ofconstituents of the panel.

[0076]FIG. 31 illustrates the effect of the pharmaceutical agent,clofibrate, as measured on a rat liver metabolism selected panel. Theprofiles for six rats are provided as indicated on the z axis. Thecontrol (baseline) is a set of rats treated only with the carriercontrol.

[0077]FIG. 32 illustrates the ability of the rat metabolism selectedpanel to differentiate drug responses (clofibrate versus benzo[a]pyrene)in Spraque-Dawley rats. Clofibrate (right hand bars) and Benzopyrene(left hand bars). The control (baseline) is a set of rats treated onlywith the carrier control.

[0078]FIG. 33 illustrates the effect of administration of a stimulant(TNF-α) as measured by a combination of constituents selected from theinflammation, skin/epithelial, and vascular selected panels. The targetis human keratinocytes in culture. The baseline is non stimulated cells.The baseline is a set of rats that were non-stimulated.

[0079]FIG. 34 illustrates the effect of administration of benzo[a]pyreneon cryo-preserved human hepatocytes over time as measured by the humanliver selected panel. The control (baseline) are cells treated similarlybut without the addition of benzo[a]pyrene.

[0080]FIG. 35 demonstrates the effect of treating human umbilical veinendothelial cells in culture with TNFα for 24 hours. The control orbaseline is established from cells handled similarly but without theaddition of the stimulant.

[0081]FIG. 36 illustrates the protective effect of the antioxidantn-acetylcysteine (NAC) on human keratinocytes in culture after exposurethe UVB energy. The dark bars indicate the effect of UVB exposure only.Cells that were treated with NAC followed by exposure to the same UVBenergy show a decreased induction of expression at most of the gene locicovered by the skin selected panel. The baseline corresponds to cellsexposed to assay media only.

DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

[0082] As used in this description and the accompanying claims, thefollowing terms shall have the meanings indicated, unless the contextotherwise requires:

[0083] A “collection of cells” is a set of cells, wherein the set has atleast one constituent.

[0084] A “population of cells” includes one or more cells. A populationof cells may refer to cells in vivo or to in vitro cultures. In vitrocultures may include organ cultures or cell cultures where cell culturesmay be primary or continuous cell cultures of eukaryotic or prokaryoticcells. Cell lines can be primary cultures or cell samples, e.g. from atumor, from blood or a blood fraction, or biopsy explants from an organ,or can be established cell lines or microbial strains.

[0085] A “region of the subject” from which proteins are obtained may(but is not required to be) the same part of the subject from which hasbeen obtained a collection of cells or a population of cells. The cellsand the proteins may both be obtained from blood of the subject, forexample. Alternatively, for example, the cells may be obtained fromblood and the proteins may be obtained from a scraping of tissue or viceversa. Similarly, the proteins may be obtained from urine of thesubject, for example, whereas the cells may be obtained elsewhere, as,for example, from blood.

[0086] A “panel” of genes is a set of genes including at least twoconstituents.

[0087] A “normative” condition of a subject to whom a composition is tobe administered means the condition of a subject before administration,even if the subject happens to be suffering from a disease.

[0088] An “expression” of a gene includes the gene product whether RNAor protein resulting from translation of the messenger RNA.

[0089] A “large number” of data sets based on a common panel of genes isa number of data sets sufficiently large to permit a statisticallysignificant conclusion to be drawn with respect to an instance of a dataset based on the same panel.

[0090] A “biological condition” of a subject is the condition of thesubject in a pertinent realm that is under observation, and such realmmay include any aspect of the subject capable of being monitored forchange in condition, such as health, disease including cancer; trauma;aging; infection; tissue degeneration; developmental steps; physicalfitness; obesity, or mood. As can be seen, the conditions may be chronicor acute or simply transient. Moreover, a targeted biological conditionmay be manifest throughout the organism or population of cells or may berestricted to a specific organ (such as skin, heart, eye or blood). Theterm “biological condition” includes a “physiological condition”.

[0091] The “blind administration” of a selected one of a composition orplacebo to a subject in a clinical trial involves administering thecomposition or placebo to the subject in accordance with a protocolpursuant to which the subject lacks knowledge whether the substanceadministered is the composition or a placebo.

[0092] An “organism” is any living cell including microorganisms,animals and plants. An animal is commonly in this context a mammal, butmay be a vertebrate non-mammal, as e.g., a zebra fish, or aninvertebrate, as, e.g. Caenorhabditis elegans.

[0093] An “agent” is a composition or a stimulus. A “stimulus” mayinclude, for example ultraviolet A or B, or light therapy for seasonalaffective disorder, or treatment of psoriasis with psoralen or treatmentof melanoma with embedded radioactive seeds, other radiation exposure,etc. A “composition” includes a chemical compound, a nutraceutical, acombination of compounds, or a complex mixture.

[0094] A “clinical indicator” is any physiological datum used alone orin conjunction with other data in evaluating the physiological conditionof a collection of cells or of an organism. This term includespre-clinical indicators.

[0095] A “selected panel” is an experimentally verified set ofconstituents, each constituent being a distinct expressed product of agene, whether RNA or protein, wherein constituents of the set areselected so that their measurement provides a measurement of a targetedbiological condition A “selected profile” is a set of values associatedwith constituents of a selected panel resulting from evaluation of abiological sample (or population of samples).

[0096] A “signature profile” is an experimentally verified subset of aselected profile selected to discriminate a biological condition, agentor physiological mechanism of action. A “signature panel” is a subset ofa selected panel, the constituents of which are selected to permitdiscrimination of a biological condition, agent or physiologicalmechanism of action.

[0097] “Distinct RNA or protein constituent” in a panel of constituentsis a distinct expressed product of a gene, whether RNA or protein.

[0098] An embodiment of the invention includes the formation ofcalibrated data sets that describe a biological condition or an effectof an agent on a biological condition. A calibrated data set representsa set of values that correspond to variations in gene expression wherethe variations are informative. This approach does not requirecomprehensive analysis of all gene expression in target cells associatedwith a particular condition. Nor is any one single gene locusnecessarily of particular significance. Rather a pattern of variation (aprofile) is sought that correlates, in a reproducible manner, with aparticular condition. There may be no a priori knowledge of acorrelation but rather a correlation may be established by evaluating apanel of constituents of reasonable size (for example up to 100constituents) and iteratively testing the gene expression profiles fordifferent subjects or for the same subject from which the mostinformative loci for a particular condition may be selected. Aninformative subgroup of constituents in a panel may be selected thatconsistently vary for a particular condition and this subgroup may thenbecome the signature panel, the signature panel giving rise to asignature profile.

[0099] In further embodiments of the invention, any calibrated data setfor an individual that has more members than reflective of a singlesignature panel may be mined for calibrated profiles that correspond toadditional signature panels, thereby potentially providing new insightsinto mechanisms of action of a biological condition on sets of genes.Measurement of changes in transcribed RNA in a cell as a result of anenvironmental change or aging is an exquisitely sensitive measure of theresponse of a cell. Techniques available today to quantify transcribedRNA in a cell add to the sensitivity of the approach. Embodiments of theinvention that are directed to patterns of change in amounts oftranscribed RNA provide a means to focus and interpret this richinformation.

[0100] In contrast to the above approach, much attention in the priorart has been directed to the sequencing of the human genome and theidentification of all the genes encoded therein. Accompanying thegrowing amount of sequence data, microarrays provide a means to surveymany hundreds to thousands of gene sequences. Microarrays are being usedto provide DNA profiles that identify mutations in an individual andthose mutations will be associated with predictions concerningdevelopment of disease in those individuals.

[0101] Transcriptomics and proteomics are now the focus of increasingattention. These studies are directed to analyzing the entire body ofRNA and protein produced by living cells. Microarrays provide a methodfor analyzing many thousands of different human RNAs as to whether theyare expressed and by which cells. For example, a project undertaken bythe National Cancer Institute and others to examine mRNAs produced byvarious types of cancer cells, have revealed 50,000 genes that areactive in one or more cancers. The goal of these studies is to identifynovel cancer drugs that are directed to knocking out or enhancing theproduction of certain proteins. (Kathryn Brown, The Human GenomeBusiness Today, Scientific American, July 2000, p.50; Julia Karow, The“Other” Genomes, Scientific American, July 2000, p.53; Ken Howard, “TheBioinformatics Gold Rush, Scientific American, July 2000, p.58; CarolEzzell, Beyond the Human Genome, Scientific American, July 2000, p.64;all incorporated by reference.) Major efforts in correlating geneticvariation of individuals and the functional interrelationships of genesin health and disease are being conducted in a variety of consortiaincluding the single nucleotide polymorphism consortium and the HumanEpigenome Consortium (Beck et al. Nature BioTechnology 17 (1999) p1144). The Epigenome Consortium plans to analyze sets of genomefragments from both healthy and diseased individuals in the 500different human tissues (Bioworld International: Dec. 22, 1999). Thisapproach seeks to correlate absolute expression of genes associated witha particular condition with the presence of that condition. Examples ofprior art that seek to measure gene expression in absolute amountsincluding by subtractive methods or by determining amounts with respectto housekeeping genes or by targeting a single gene expression systemare U.S. Pat. No. 5,643,765; U.S. Pat. No. 5,811,231; U.S. Pat. No.5,846,720; U.S. Pat. No. 5,866,330; U.S. Pat. No. 5,968,784; U.S. Pat.No. 5,994,076; WO 97/41261; WO 98/24935; WO 99/11822; WO 99/44063; WO99/46403; WO 99/57130; WO00/22172 and. WO00/11208.

[0102] We have taken a different and novel approach to the above byidentifying reproducible patterns of gene expression that areinformative by virtue of the degree of variation between a sample and abaseline, for example, in a subject with the condition and a subjectwithout the condition. The variations may be correlated with othernon-genetic indications such as clinical indicators (for humans) of atraditional nature but are not required per se to be causative.Accordingly, the amount of gene expression product (for example RNAtranscript) produced by a gene locus in a cell under certaincircumstances is measured and then stored as a value in a first profiledata set. This value is calibrated with respect to a second value (abaseline profile data set) to provide a member of a calibrated profiledata set. The values recorded for the profile data set, relying on aparticular baseline data set to produce a calibrated data set, becomepart of the descriptive record; any or all of these results can bestored in a database which may be accessed through a global network. Inthis way any new data in the form of a profile data set or a calibratedprofile data set measured at any global location can be directlycompared to an archive of descriptive records including calibratedprofile data sets and baseline data sets so as to extend the storedlibrary of profiles and provide predictive, diagnostic, or evaluativedata about a particular biological condition or agent.

[0103] We have exemplified the use of selected panels of constituentscorresponding to gene loci from which quantitative gene expression isdetermined by, for example, quantitatively measuring the transcribed RNAin a sample of a subject, for applications that include: (a) measurementof therapeutic efficacy of natural or synthetic compositions or stimulithat may be formulated individually or in combinations or mixtures for arange of targeted physiological conditions; (b) predictions oftoxicological effects and dose effectiveness of a composition or mixtureof compositions for an individual or in a population; (c) determininghow two or more different agents administered in a single treatmentmight interact so as to detect any of synergistic, additive, negative,neutral or toxic activity (d) performing pre-clinical and clinicaltrials by providing new criteria for pre-selecting subjects according toinformative profile data sets for revealing disease status andconducting preliminary dosage studies for these patients prior toconducting phase 1 or 2 trials. Gene expression profiling may be used toreduce the cost of phase 3 clinical trials and may be used beyond phase3 trials; (e) labeling for approved drugs; (f) selection of suitablemedication in a class of medications for a particular patient that isdirected to their unique physiology; (g) diagnosing or determining aprognosis of a medical condition or an infection which may precede onsetof symptoms or alternatively diagnosing adverse side effects associatedwith administration of a therapeutic agent; (h) managing the health careof a patient; and (i) quality control for different batches of an agentor a mixture of agents.

[0104] The Subject

[0105] The methods herein can be applied to a subject that includes anyliving organism where a living organism includes a prokaryote such as abacterium or a eukaryote including single celled eukaryotic organisms atone end of the spectrum and humans at the other and everything inbetween including plants. The figures relate to calibrated profile datasets obtained from humans and mammals. Nonetheless, the methodsdisclosed here may be applied to cells of other organism without theneed for undue experimentation by one of ordinary skill in the artbecause all cells transcribe RNA and it is known in the art how toextract RNA from all types of cells.

[0106] A tissue sample may include a single cell or multiple cells orfragments of cells. Body fluid includes blood, urine, spinal fluid,lymph, mucosal secretions, hemolymph or any other body fluid known inthe art for a subject. For an animal subject, a tissue or fluid samplemay be obtained by means of a biopsy needle aspirate, a lavage sample,scrapings and surgical incisions or other means known in the art.

[0107] Selected Panels

[0108] Steps in selecting constituents in a selected panel may includesearching publicly available medical literature for RNA or proteins orsets of RNAs or proteins that directly or indirectly vary with aparticular biological condition. A selected panel containing up to 100constituents may be selected. According to the condition being examined,just a small subset of the selected panel constituents may beinformative. In determining membership of the selected panel of genes,it is not necessary for the panel to be an exhaustive selection. Ratherit is desired to obtain from the selected panel an expression profilethat discriminates consistently with respect to the targetedphysiological or biological condition. Moreover, a selected panel is notnecessarily selected according to an expected profile of gene expressionin cells that directly respond to a biological effect. For example, geneexpression associated with liver metabolism may be analyzed in a bloodsample. FIGS. 20 and 22 provide calibrated profiles of whole bloodtreated with herbal agents using markers for liver metabolism.

[0109] The number of constituents in a selected panel can vary.According to the examples provided below, selected panels of up to 24-96genes are selected for evaluating expression levels. Although a selectedpanel may be as large as 100 constituents, it is desirable for aparticular selected panel to have no more than 24 constituents, moreparticularly, less than 12 constituents. For example, subsets of no morethan 8 genes have been used that may be derived from a larger panel butwhich are sufficiently informative to effectuate discrimination. Thenumber of constituents in a selected panel for which expression ismonitored may vary widely depending on the context. For example, FIG. 1describes data acquisition from in vitro cell culture and from animaltoxicology studies, which includes expression of about 25 to 100 or moregenes. In contrast, selection of markers or surrogate markers include,for example, three to 100 genes, preferably five to 50 or five to 25genes to be analyzed from samples obtained in clinical studies. In thismanner markers or surrogate markers having predictive value for amedical condition, such as a genetic predisposition, a response totherapeutic agent, an inflammatory condition, or an infection, etc. canbe identified and cumulatively larger populations can be obtained torefine the correlations. A health profile can then be generated for anindividual subject using a low volume blood sample. The blood sample canbe analyzed for expression profile data of about 100-500 genes,comprising markers or surrogate markers of a number of medicalconditions (FIG. 1: right panel). Selected panels of varying sizes maybe utilized as necessary and subsequent refinements in methodology maylead to selection of subsets having selected panels as large as 15 genesor 12 genes or as small as 6, 5, 4, 3 or 2 genes.

[0110] We have found that we can measure concentrations of constituentsin selected panels in a manner that is both highly precise andreproducible in samples taken from the same individual under the sameconditions. We have similarly found that such concentration measurementsare reproducible in samples that are repeatedly tested.

[0111] We commonly run a sample through a panel in quadruplicate; thatis, a sample is divided into aliquots and for each aliquot we measureconcentrations of each constituent in a selected panel. Over a total of900 constituent assays, with each assay conducted in quadruplicate, wefound an average coefficient of variation, (standarddeviation/average)*100, of less than 1 percent among results for eachassay. This figure is a measure of what we call “intra-assayvariability”. We have also conducted assays on different occasions usingthe same sample material. With 72 assays, resulting from concentrationmeasurements of constituents in a panel of 24 members, and suchconcentration measurements determined on three different occasions overtime, we found an average coefficient of variation of less than 2percent. We regard this as a measure of what we call “inter-assayvariability”.

[0112] We have found it valuable in using the quadruplicate test resultsto identify and eliminate data points that are statistical “outliers”;such data points are those that differ by a percentage greater, forexample, than 3% of the average of all four values and that do notresult from any systematic skew that is greater, for example, than 1%.Moreover, if more than one data point in a set of four is excluded bythis procedure, then all data for the relevant constituent is discarded.

[0113] As discussed in further detail below under “Gene Expression”, wehave found it valuable to optimize the efficiency of amplification forall constituents of a panel in a manner to achieve comparableamplification efficiencies (that is, amplification efficiencies that aresubstantially similar as described below under “Gene Expression”) forall constituents, so that precise quantification of gene expression ofall panel constituents may be determined consistently on successiveoccasions. In this manner, there may result data that is useful becauseit is precise and reliable.

[0114] What this approach means, among other things, is that byutilizing a relatively small panel, and by controlling amplificationefficiency and other parameters, we create a panel that is uniquelyinformative. This approach differs from prior art endeavors wherespecificity is optimized only on a per-constituent basis and reactionconditions are not optimized for the panel as a whole.

[0115] It is envisaged that any single biological condition may bedescribed by a signature panel having a small number of highlyinformative constituents providing a signature calibrated profile (alsoreferred to as a fingerprint). The presence of highly informative lociis demonstrated in several of the accompanying figures. For example,FIG. 11(a) Il-2, Il-4 and Il-5 are highly informative. Highlyinformative constituents in FIG. 21 include thepro-inflammatory-interleukins. The signature panel may provide asignature profile or fingerprint which is sufficiently robust to serveas a standard in describing a particular biological condition or aneffect of a particular agent on a biological condition

[0116] For purposes of illustrating a signature panel, constituents of aselected panel for measuring inflammation have been provided that areinformative with respect to a particular biological condition. Forexample, we have used a selected panel for inflammation that has 6constituents—Il-1α, Il-6, Il-8, Il-18, GMCSF and IFNγ in FIG. 18(a)-(e)to determine the response of 5 subjects to varying concentrations ofdrugs. This group of constituents is a subset of a larger selected panelof inflammation related gene loci such as shown in FIG. 19a and FIG. 19bwhere the Inflammation Selected Panel includes Il-α, Il-β, Il-2, Il-3,Il-4, Il-6, Il-7, Il-8, Il-10, Il-12p40, Il-15, Il-15, Il-18, GM-CSF,Ifn-gamma, TGF-β, cox-2, ICE, MMP-9, ICAM, TNF-α and TNF-β. The subsetof constituents were selected on the basis of the information soughtconcerning the biological condition.

[0117] Embodiments of the invention provide examples of numerousdifferent selected panels which may be used separately or together.These selected panels include an Inflammation Selected Panel (Table 1) aCell Growth and Differentiation Selected Panel (Table 2), a LiverMetabolism and Toxicity Selected Panel (Table 3). We have developedadditional selected panels including Skin Response Selected Panel (Table4), Prostate Selected Panel (Table 5) (for measuring prostate health anddisease), Vascular Selected Panel (Table 6) (for measuring condition ofthe vascular system and endothelial cells). It is a significant propertyof each of these selected panels that measurement of the selectedpanel's constituents provides a measurement of the physiologicalcondition to which the selected panel is targeted. Selected panels mayalso provide useful information concerning gene response outside thetarget condition. In these tables the left-hand column identifies theparticular gene loci, and the right-hand column describes proteinsexpressed by these loci. However, as described in detail below,embodiments of the present invention may utilize, for example, mRNA orprotein expression products as constituents. While below we provideexamples based primarily on the Inflammation Selected Panel and subsetsof it, the approaches set forth herein are equally applicable to theother selected panels described above. Although provided as examples,the above selected panels are not intended to be limiting.

[0118] Gene Expression

[0119] For measuring the amount of a particular RNA in a sample, we haveused methods known to one of ordinary skill in the art to extract andquantify transcribed RNA from a sample with respect to a constituent ofa selected panel (See detailed protocols below.) Briefly, RNA isextracted from a sample such as a tissue, body fluid (see Example 11below), or culture medium in which a population of a subject might begrowing. For example, cells may be lysed and RNA eluted in a suitablesolution in which to conduct a DNAse reaction. First strand synthesis(see Example 10 below) may then be performed using a reversetranscriptase. Gene amplification, more specifically quantitative PCRassays, can then be conducted and the gene of interest size calibratedagainst a marker such as 18S rRNA (Hirayama et al., Blood 92, 1998:46-52). Samples are measured in multiple duplicates, for example, 4replicates. Relative quantitation of the mRNA is determined by thedifference in threshhold cycles between the internal control and thegene of interest (see Example 12 below). In an embodiment of theinvention, quantitative PCR is performed using amplification, reportingagents and instruments such as those supplied commercially by AppliedBiosystems (Foster City, Calif.). Given a defined efficiency ofamplification of target transcripts, the point (e.g., cycle number) thatsignal from amplified target template is detectable may be directlyrelated to the amount of specific message transcript in the measuredsample. Similarly, other quantifiable signals such as fluorescence,enzyme activity, disintegrations per minute, absorbance, etc., whencorrelated to a known concentration of target templates (e.g., areference standard curve) or normalized to a standard with limitedvariability can be used to quantify the number of target templates in anunknown sample.

[0120] Although not limited to amplification methods, quantitative geneexpression techniques may utilize amplification of the targettranscript. Alternatively or in combination with amplification of thetarget transcript, amplification of the reporter signal may also beused. Amplification of the target template may be accomplished byisothermic gene amplification strategies, or by gene amplification bythermal cycling such as PCR.

[0121] It is desirable to obtain a definable and reproduciblecorrelation between the amplified target or reporter and theconcentration of starting templates. We have discovered that thisobjective can be achieved by careful attention to, for example,consistent primer-template ratios and a strict adherence to a narrowpermissible level of amplification efficiencies (for example 99.8 to100% relative efficiency). For example, in determining gene expressionlevels with regard to a single selected profile, it is necessary thatall constituents of the panels maintain a similar and limited range ofprimer template ratios (for example, within a 10-fold range) andamplification efficiencies (within, for example, less than 1%) to permitaccurate and precise relative measurements for each constituent. Weregard amplification efficiencies as being “substantially similar”, forthe purposes of this description and the following claims, if theydiffer by no more than approximately 10%. Preferably they should differby less than approximately 2% and more preferably by less thanapproximately 1%. These constraints should be observed over the entirerange of concentration levels to be measured associated with therelevant biological condition. In practice, we run tests to assure thatthese conditions are satisfied. For example, we typically design andmanufacture a number primer-probe sets, and determine experimentallywhich set gives the best performance. Even though primer-probe designand manufacture can be enhanced using computer techniques known in theart, and notwithstanding common practice, we still find thatexperimental validation is useful. Moreover, in the course ofexperimental validation, we associate with the selected primer-probecombination a set of features:

[0122] (i) The reverse primer should be complementary to the coding DNAstrand; located across an intron-exon junction, with not more than threebases of the three-prime end of the reverse primer complementary to theproximal exon. (If more than three bases are complementary, then itwould tend to competitively amplify genomic DNA.)

[0123] (ii) The primer probe should amplify cDNA of less than 110 basesin length.

[0124] (iii) The primer probe should not amplify genomic DNA ortranscripts or cDNA from related but biologically irrelevant loci.

[0125] A suitable target of the selected primer probe is first strandcDNA, which may be prepared, in one embodiment, according to Example 1below. In Example 11 below, we illustrate use of the primer probe withthe first strand cDNA of Example 1 to permit measurement of constituentsof a selected panel.

[0126] It is envisaged that techniques in the art using microfluidicsfor example and highly sensitive markers will enable quantitation of RNAto occur directly from a single cell or lysed cell. This may rely onamplification of a marker but may not require amplification of thetranscripts themselves. The amount of transcript measured for anyparticular locus is a data point or member of the first profile data setfor a particular selected panel.

[0127] According to embodiments of the invention, a first profile dataset is derived from the sample, the first profile data set including aplurality of members, each member being a quantitative measure of theamount of a RNA transcribed from a gene locus; the gene locus being aconstituent in a panel of constituents. A first profile data set may beobtained from a quantitative measure of the amount of a distinct RNA orprotein corresponding to a gene locus. The figures provided here aredirected to RNA. However, methods herein may also be applied usingproteins where sensitive quantitative techniques, such as an EnzymeLinked ImmunoSorbent Assay (ELISA), are available and well-known in theart for measuring the amount of a protein constituent.

[0128] Baseline Profile Data Sets

[0129] The analyses of samples from single individuals and from largegroups of individuals provide a library of profile data sets relating toa particular panel or series of panels. These profile data sets may bestored as records in a library for use as baseline profile data sets. Asthe term “baseline” suggests, the stored baseline profile data setsserve as comparators for providing a calibrated profile data set that isinformative about a biological condition or agent. Baseline profile datasets may be stored in libraries and classified in a number ofcross-referential ways. One form of classification may rely on thecharacteristics of the panels from which the data sets are derived.Another form of classification may be by particular biologicalcondition. The concept of biological condition encompasses any state inwhich a cell or population of cells may be found at any one time. Thisstate may reflect geography of samples, sex of subjects or any otherdiscriminator. Some of the discriminators may overlap. The libraries mayalso be accessed for records associated with a single subject orparticular clinical trial. The classification of baseline profile datasets may further be annotated with medical information about aparticular subject, a medical condition, a particular agent etc.

[0130] The choice of a baseline profile data set for creating acalibrated profile data set is related to the biological condition to beevaluated, monitored, or predicted, as well as, the intended use of thecalibrated panel, e.g., as to monitor drug development, quality controlor other uses. It may be desirable to access baseline profile data setsfrom the same subject for whom a first profile data set is obtained orfrom different subject at varying times, exposures to stimuli, drugs orcomplex compounds; or may be derived from like or dissimilarpopulations.

[0131] The profile data set may arise from the same subject for whichthe first data set is obtained, where the sample is taken at a separateor similar time, a different or similar site or in a different orsimilar physiological condition. For example, FIG. 5 provides a protocolin which the sample is taken before stimulation or after stimulation.The profile data set obtained from the unstimulated sample may serve asa baseline profile data set for the sample taken after stimulation. Thebaseline data set may also be derived from a library containing profiledata sets of a population of subjects having some definingcharacteristic or biological condition. The baseline profile data setmay also correspond to some ex vivo or in vitro properties associatedwith an in vitro cell culture. The resultant calibrated profile datasets may then be stored as a record in a database or library (FIG. 6)along with or separate from the baseline profile data base andoptionally the first profile data set although the first profile dataset would normally become incorporated into a baseline profile data setunder suitable classification criteria.

[0132] Selected baseline profile data sets may be also be used as astandard by which to judge manufacturing lots in terms of efficacy,toxicity, etc. Where the effect of a therapeutic agent is beingmeasured, the baseline data set may correspond to gene expressionprofiles taken before administration of the agent. Where quality controlfor a newly manufactured product is being determined, the baseline dataset may correspond with a gold standard for that product. However, anysuitable normalization techniques may be employed. For example, anaverage baseline profile data set is obtained from authentic material ofa naturally grown herbal nutraceutical and compared over time and overdifferent lots in order to demonstrate consistency, or lack ofconsistency, in lots of compounds prepared for release.

[0133] Calibrated Data

[0134] A calibrated profile data set may be described as a function of amember of a first profile data set and a corresponding member of abaseline profile data set for a given gene locus in a panel. Forexample, calibrated profile data sets may be derived by calculating aratio of the amount of RNA transcribed for a panel constituent in a cellsample in an environmental including intervention such as a therapeutictreatment or at a particular time (first profile data set) with respectto the amount of RNA transcribed for the same panel constituent in acell that differs in some manner from the sample (baseline profile dataset) (FIGS. 5 and 6). Given the precision we have achieved inmeasurement of gene expression, described above in connection with“selected panels” and “gene amplification”, we conclude that wheredifferences occur in measurement under such conditions, the differencesare attributable to differences in biological condition. Thus we havefound that calibrated profile data sets are highly reproducible insamples taken from the same individual under the same conditions. Wehave similarly found that calibrated profile data sets are reproduciblein samples that are repeatedly tested. We have also found repeatedinstances wherein calibrated profile data sets obtained when samplesfrom a subject are exposed ex vivo to a compound are comparable tocalibrated profile data from a sample that has been exposed to a samplein vivo (FIG. 14, FIG. 16(a), (b), and FIGS. 29(a) and 29(b)). We havealso found, importantly, that an indicator cell line treated with anagent can in many cases provide calibrated profile data sets comparableto those obtained from in vivo or ex vivo populations of cells (FIG.15). Moreover, we have found that administering a sample from a subjectonto indicator cells can provide informative calibrated profile datasets with respect to the biological condition of the subject includingthe health, disease states, therapeutic interventions, aging or exposureto environmental stimuli or toxins of the subject (FIG. 25).

[0135] A use of a calibrated profile data set is to evaluate abiological condition of a subject. This may be for purposes of diagnosisor prognosis of a clinical disorder. It is desirable to obtain acalibrated data set that describes a state of health or alternatively astate of age or body mass or any condition or state that an individualsubject might find themselves to be in. For example, the biologicalcondition may relate to physical activity, conditioning or exercise,mental state, environmental factor such as medication, diet, orgeography or exposure to radiation or environmental contamination orinfectious agent, biological or environmental toxin. If health orconversely a clinical disorder is being evaluated, calibrated profilesdata sets may be used for monitoring change in health status by periodicor regular comparison of profiles; the disorder may be a complex diseaseprocess possibly involving multiple gene including inflammation,autoimmune disease, degenerative disease, allergy, vascular disease,ischemia, developmental disease, hormonal conditions and infectiousdiseases. The clinical disorder may further include arthritis, asthma,multiple sclerosis and perimenopausal changes. The biological conditionmay affect a system of a subject including a respiratory, vascular,nervous, metabolic, urinary, reproductive, structural and immunologicalsystem or other metabolic state. The above examples of a biologicalcondition are given by way of illustration and are not intended to belimiting.

[0136] Similarly, calibrated profile data sets may be used to measure,monitor or predict the host response to an infectious agent for purposesof identifying the infectious agent, assessing the duration ofinfection, the extent of exposure or making therapeutic decisions.

[0137] The evaluation of activity of an agent may require a series ofcalibrated profiles. It is here shown that calibrated profile data setsmay be used to describe the biological activity of an agent that may bea single compound or a complex compound such as a nutraceutical orherbal. The agent may be assayed using indicator cells, ex vivo cellpopulations or by in vivo administration. These assays may rely on aseries of signature panels or enlarged panels for different biologicalconditions. The resultant calibrated profiles may then be used to inferlikely in vivo activity from the in vitro study. Insights into toxicityand mechanisms of action can also be inferred from calibration profiledata sets. For example, the herbal Echinacea is believed to have bothimmunostimulatory and anti-inflammatory properties although neither hasbeen measured systematically. We have provided a systematic approach toinvestigate the biological activities of these and other herbs. Weinvestigated the alleged immunostimulatory properties of the herbs bycomparing the effect of treating the indicator cell line THP-1 orperipheral blood cells with the agent to untreated cells. Untreatedcells include LPS stimulated untreated cells. Untreated cells were usedas a baseline profile data set to measure the difference in geneexpression between a baseline profile data set and the experimentaltreatment with the compound. Baseline profile data sets included asingle sample or an average value from a series of experiments. Theresultant calibrated profile data sets could then be compared with alibrary of calibrated profile data sets for a particular herb or/andlibraries associated with different agents or conditions.

[0138] From the information obtained about a previously undescribedagent, a signature panel may be derived optionally together with asignature profile to serve as a gold standard for testing other batchesof the same agent.

[0139] Calculation of Calibrated Profile Data Sets and ComputationalAids

[0140] The function relating the baseline and profile data sets is, inan embodiment of the invention, a ratio expressed as a logarithm. Thecalibrated profile data set may be expressed in a spreadsheet orrepresented graphically for example, in a bar chart or tabular form butmay also be expressed in a three dimensional representation. Theconstituent may be itemized on the x-axis and the logarithmic scale maybe on the y-axis. Members of a calibrated data set may be expressed as apositive value representing a relative enhancement of gene expression oras a negative value representing a relative reduction in gene expressionwith respect to the baseline.

[0141] Each member of the calibrated profile data set should bereproducible within a range with respect to similar samples taken fromthe subject under similar conditions. For example, the calibratedprofile data sets may be reproducible within one order of magnitude withrespect to similar samples taken from the subject under similarconditions. More particularly, the members may be reproducible within50%, more particularly reproducible within 20%, and sometimes even 10%.In accordance with embodiments of the invention, a pattern ofincreasing, decreasing and no change in relative gene expression fromeach of a plurality of gene loci examined in the precision panel may beused to prepare a calibrated profile set that is informative withregards to a biological condition, biological efficacy of an agenttreatment conditions or for comparison to populations. Patterns of thisnature may be used to identify likely candidates for a drug trial, usedin combination with other clinical indicators to be diagnostic orprognostic with respect to a biological condition or may be used toguide the development of a pharmaceutical or nutraceutical throughmanufacture, testing and marketing.

[0142] The numerical data obtained from quantitative gene expression andnumerical data from calibrated gene expression relative to a baselineprofile data set may be stored in databases or digital storage mediumsand may retrieved for purposes including managing patient health care orfor conducting clinical trials or for characterizing a drug. The datamay be transferred in networks via the World Wide Web, email, orinternet access site for example or by hard copy so as to be collectedand pooled from distant geographic sites (FIG. 8).

[0143] In an embodiment of the present invention, a descriptive recordis stored in a single database or multiple databases where the storeddata includes the raw gene expression data (first profile data set)prior to transformation by use of a baseline profile data set, as wellas a record of the baseline profile data set used to generate thecalibrated profile data set including for example, annotations regardingwhether the baseline profile data set is derived from a particularsignature panel and any other annotation that facilitates interpretationand use of the data.

[0144] Because the data is in a universal format, data handling mayreadily be done with a computer. The data is organized so as to providean output optionally corresponding to a graphical representation of acalibrated data set.

[0145] For example, a distinct sample derived from a subject being atleast one of RNA or protein may be denoted as P_(i). The first profiledata set consists of M_(j) where Mj is a quantitative measure of adistinct RNA or protein constituent. The record Ri is a ratio of M and Pand may be annotated with additional data on the subject relating to forexample, age, diet, ethnicity, gender, geographic location, medicaldisorder, mental disorder, medication, physical activity, body mass andenvironmental exposure. Moreover, data handling may further includeaccessing data from a second condition database which may containadditional medical data not presently held with the calibrated profiledata sets. In this context, data access may be via a computer network.

[0146] The above described data storage on a computer may provide theinformation in a form that can be accessed by a user. Accordingly, theuser may load the information onto a second access site includingdownloading the information. However, access may be restricted to usershaving a password or other security device so as to protect the medicalrecords contained within. A feature of this embodiment of the inventionis the ability of a user to add new or annotated records to the data setso the records become part of the biological information.

[0147] The graphical representation of calibrated profile data setspertaining to a product such as a drug provides an opportunity forstandardizing a product by means of the calibrated profile, moreparticularly a signature profile. The profile may be used as a featurewith which to demonstrate relative efficacy, differences in mechanismsof actions, etc. compared to other drugs approved for similar ordifferent uses.

[0148] The various embodiments of the invention may be also implementedas a computer program product for use with a computer system. Theproduct may include program code for deriving a first profile data setand for producing calibrated profiles. Such implementation may include aseries of computer instructions fixed either on a tangible medium, suchas a computer readable medium (for example, a diskette, CD-ROM, ROM, orfixed disk), or transmittable to a computer system via a modem or otherinterface device, such as a communications adapter coupled to a network.The network coupling may be for example, over optical or wiredcommunications lines or via wireless techniques (for example, microwave,infrared or other transmission techniques) or some combination of these.The series of computer instructions preferably embodies all or part ofthe functionality previously described herein with respect to thesystem. Those skilled in the art should appreciate that such computerinstructions can be written in a number of programming languages for usewith many computer architectures or operating systems. Furthermore, suchinstructions may be stored in any memory device, such as semiconductor,magnetic, optical or other memory devices, and may be transmitted usingany communications technology, such as optical, infrared, microwave, orother transmission technologies. It is expected that such a computerprogram product may be distributed as a removable medium withaccompanying printed or electronic documentation (for example, shrinkwrapped software), preloaded with a computer system (for example, onsystem ROM or fixed disk), or distributed from a server or electronicbulletin board over a network (for example, the Internet or World WideWeb). In addition, a computer system is further provided includingderivative modules for deriving a first data set and a calibrationprofile data set.

[0149] Clinical Trials

[0150] The use of calibrated profile data sets for performing clinicaltrials is illustrated in FIG. 10 using the above-described methods andprocedures for running a clinical trial or managing patient care.Moreover, standardization between laboratories may be achieved by usinga particular indicator cell line such as THP-1 which is stimulated by aknown stimulator such as lipopolysaccharide so that resultant profileacts as a measure that the laboratory is performing the protocolcorrectly. Of course this is one single example, and other cells lines,tissues, or biological samples or combinations of the foregoing may beused as standards.

[0151] A further embodiment of the invention provides a method forpatient selection for augmenting clinical trials. Clinical trials inwhich candidate subjects are included or excluded according to apredetermined optimum calibrated profile for a given biologicalcondition can result in more precise monitoring than would be otherwisepossible. It can also result in a greater efficiency in clinical trialdesign because unsuitable patients that have for example complicatingfactors or conditions can be screened out. The calibrated profile datawill also enhance the “signal to noise” by removing non-responders fromclinical studies. The basic structure of a clinical trial design usinggene expression profiling may follow any of several formats. Theseinclude testing body fluid from a candidate patient in the trial ex vivoagainst a new therapeutic agent and analyzing the calibrated profileswith respect to an agent-treated and placebo-treated samples using apredetermined selected panel and evaluating whether the candidatepatient would be likely to respond without adverse effects to thecomposition being tested. In selected indications, profile data obtainedfrom in vitro cell cultures or organ cultures may be desired where thecell originates from a target subject or from another subject or from anestablished cell line, or from a cell samples removed from the targetsubject where the cell samples may be obtained from any body fluidincluding a blood, urine, semen, amniotic, or a cerebrospinal fluidsample, or from a scraping from mucosal membranes such as from thebuccal cavity, the eye, nose, vagina or by means of a biopsy includingepithelial, liver, sternum marrow, testicular, or from tumor tissueremoved surgically from a tumor at any location. The above-describedsources of samples are applicable to any medical use in which calibratedprofile data sets are desired.

[0152] In vitro dosage and toxicity studies using calibrated profiledata sets obtained from indicator cell lines or samples of the patienttested ex vivo may provide useful information prior to initiation of theclinical trial and may significantly reduce the cost and time of aclinical trial while increasing the likelihood of identifying thepresence of beneficial effect(s). In particular, the dose may beoptimized on an individualized basis to maximize the impact ontherapeutic outcome. For example, FIG. 12 shows how ex vivo blood cellsrespond to the stimulatory effect of LPS and the subsequent treatmentwith an anti-inflammatory drug (methotrexate, meclofenamate ormethylprednisolone). The data show how the effect of methotrexate andmeclofenamate generates similar calibrated profile data sets where thebaseline is LPS treated blood. In contrast, methylprednisolone has asubstantially different effect from the other two compounds. A similartype of analysis can be performed with complex mixtures, as illustratedin FIG. 21, in which the calibrated profiles obtained when Echinacea,Arnica and Siberian Ginseng applied to LPS stimulated blood ex vivo arecompared. In this example, all three agents appear to act differentlyfrom each other with respect to a sample from a single subject. Similaranalyses can be used to compare compounds with unknown targets oractivities or metabolic patterns to compounds, complex or simple, withknown or pre-determined profiles.

[0153] The above methods and procedures may be utilized in the designand running of clinical trials or as a supplemental tool. Moreover, theabove methods and procedures may be used to monitor the patients' healthas well as the patient's responsiveness to an agent before during andafter the clinical trial. This includes monitoring whether multipleagents interfere with each other, act synergistically or additively orare toxic or neural with respect to each other. This type of informationis very important as individuals take an increasing number ofmedications.

[0154] Similarly, the methods and procedures described above may be usedto manage patient care for an individual or a population. Such methodsand procedures may also be used to develop a regional or global researchnetwork that uses calibrated profile data sets and the resultingdatabases to conduct research or trials.

[0155] Both the calibration profile data sets in graphical form and theassociated databases together with information extracted from both arecommodities that can be sold together or separately for a variety ofpurposes. For example, graphic representations of calibration profiledata sets may provide a description of a product with respect to itsactivity that may be used to promote the product. Alternatively, thegraphical form of the calibrated profile data sets and access tobaseline profile databases provide a means for manufacturers to testdiscrete batches of product against a gold standard.

[0156] The data may be used strategically for design of clinical trials.It may also be useful for physicians practicing at remote sites to offerpersonalized healthcare to a patient. Accordingly, the physician may setup personalized databases for calibrated profile data sets prior to andafter treatment of a particular condition. New data on the subject couldbe added to the personalized database at each visit to the doctor. Thedata may be generated at remote sites by the use of kits that permit aphysician to obtain a first profile data set on a sample from a patient.For remote users to access the site, it is envisaged that secured accessto the global network containing libraries of baseline profile data setsand calibrated profile data sets, classified by particular criteria andrepresenting data from larger populations than a single individual,would be necessary. The access to the global database may be passwordprotected thereby protecting the database from corrupted records andsafeguarding personal medical data. The graphical form provided by thecalibrated data sets may be used to create catalogs of compounds in apharmacopiae complete with toxic effects that might arise for particularindividuals as well as other types of drug interactions.

[0157] Access to the global database may include the option to loadselected data onto a second access site. This process may includedownloading the information to whatever site is desired by the user andcould include securing hard copies of information. It is desirable tocontrol how and what data is offloaded or copied to maintain theintegrity of the database. It is envisaged that while a global networkof clinical data would be an informational resource, it would haveutility in conducting research that may include epidemiological studiesand studies concerning the mechanism of action of an agent, as well asstudies concerning the nature of interpersonal variability as determinedby calibrated profile data sets.

[0158] Examples of Medical Uses

[0159] (a) Early detection of infectious diseases: Markers or surrogatemarkers from mice may be obtained for measuring gene expression inhumans that indicate early or immediate response to infection, forexample, to a virus such as hepatitis virus, or to a bacterium such asMycobacterium tuberculosis (the etiologic agent of tuberculosis) (seeFIG. 4). Candidate genes are identified and changes in expression ofthose genes in the presence of a challenge provide a set of markers. Theset of markers can combine markers encoded by the genome of the subjectand one more distinctive markers encoded by the genome of the infectiousagent. For example, changes in expression of an immediate early gene ofa virus, e.g. a gene encoding an enzyme of viral replication, and a hostgene such as the gene for any or all of IL-2, IL-4 and IL-5, maycomprise markers or surrogate markers for a medical condition capable ofdetecting that condition prior to the onset of medical symptoms. Thismethod may afford earlier detection of an infection than is possibleusing current diagnostic techniques.

[0160] (b) Toxicity profiles and mechanistic profiles obtained from anin vitro assay and in vivo assays. Toxicity and mechanistic informationarising from the administration of a compound to a population of cellsmay be monitored using calibrated profile data sets. The following is anexample of an experimental protocol for obtaining this information.Firstly, an experimental group is established: (1) control cellsmaintained without therapeutic agent and without stimulus; (2) cellstreated with therapeutic agent but without stimulus; (3) cells withouttherapeutic agent but with stimulus, (4) sample with therapeutic agentand with stimulus. The population of cells can be selected from primarycell cultures prepared in culture plates using methods well establishedin the art; or mature differentiated cell preparation from whole bloodor isolated monocytes from the target organism.

[0161] The cells are stimulated so as to present a targetedphysiological condition by pretreatment with LPS purified from aGram-negative bacterium (a variety of LPS preparations from pathogenicbacteria, for example, from Salmonella typhimurium and from Escherichiacoli O1157:H7, are available from Sigma, St. Louis, Mo.). Thetherapeutic agent administered to the cell samples in this example is aninhibitor of an enzyme known to be key in disease etiology, namely aninhibitor of a protease or a nucleic acid polymerase. Followingtreatment by addition of the therapeutic agent and further incubationfor four to six hours, samples of the cells are harvested and analyzedfor gene expression. Nucleic acid, specifically mRNA, can be preparedfrom the sample by methods known to one or ordinary skill in the art(see, for example, the Lyse-N-Go™ reagent, Pierce Chem. Co., Rockford,Ill.). Samples are analyzed by QPCR according to a quantitativereplicative procedure, (for example, quantitative polymerase chainreaction procedure (QPCR)) (see, for example, Gibson, U. 1996 GenomeRes. 6:995-1001, and references cited therein). Total RNA was assessedusing universal primers. Toxicity of the agent for cells can be measuredin untreated cells by vital stain uptake, rate of DNA synthesis(autoradiography of labeled nucleic compared to cells stained), stain byDNA-specific eyes (Hoechst), etc. Mechanistic profiles can be determinedby analysis of the identifies of de novo up- or down-regulated genes.Further, in the presence of a therapeutic agent, some genes are notexpressed or differentially expressed, indicating potential efficacy ofthe therapeutic agent in suppressing the effects of stimulation by theLPS. For example, in FIG. 21, levels of ICE that are somewhat stimulatedin the presence of LPS+Echinacea are substantially depressed byLPS+Arnica relative to LPS stimulated cells absent agent. Levels of HSP70 which are depressed in the presence of LPS+Echinacea aresubstantially stimulated in the presence of LPS+Arnica, and LPS+SiberianGinseng relative to LPS stimulated cells absent the addition of anagent. Levels of IL-12p40 which are slightly increased in the presenceof LPS+Echinacea are substantially depressed in the presence ofLPS+Arnica and LPS+Siberian Ginseng relative to LPS stimulation.Similarly, FIG. 16 shows a much enhanced reduction of gene expression inwhole blood for IL-1α, Il-10, Il-7, Il-10, IL-IL-15, IFN-γ, TGF-β, TNF-βcox-2, and ICAM in the presence of prednisolone+LPS when compared toarnica+LPS or nothing+LPS.

[0162] (c) Quantitation of Gene Expression in a Blood Cell to PredictToxicity in Another Tissue or Organ.

[0163] Leukocytes, for example, may be obtained from a blood sample of asubject, for the purpose of assessing the appearance of a pathologicalcondition in another organ, for example, the liver. A profile data setis obtained of genes expressed in the leukocytes, for example, genesencoding a set of lymphokines and cytokines. The data set is compared tothat of the database, to examine correlations, for example to othersubjects, and to the subject prior to administration of a therapeuticagent.

[0164] By this method, a correlation can be drawn between, for example,administration of acetaminophen (Tylenol) and sensitivity to thistherapeutic agent and manifested by liver damage. An early prediction oftherapeutic agent sensitivity, detected prior to the onset of actualdamage to the liver, may be clinically available so that the subjectreceives no further administration of acetaminophen. The database may beused to detect a correlation or correlations prior to the onset oftraditional medical assessments, such as increase in bilirubin level orother indication of liver pathology.

[0165] (d) Calibrated Profiles from Blood Cells for Prognosis ofSeverity and Prediction of Adverse Reactions in Treatment of anAutoimmune Disease.

[0166] The probability and timing of onset of symptoms of an autoimmunedisease, for example, rheumatoid arthritis, may be monitored byappearance of expression of markers or surrogate markers as determinedby the methods of gene expression profiling of markers or surrogatemarkers and comparison to a profile database as described above. Thus anindication of onset may be obtained, and advance management byutilization of preventive measures to forestall onset, can be taken.Further, the user may choose a set of potential therapeutic agents, andassess for a given agent, the probability that a subject will present anadverse reaction if given a full course of treatment, prior to that fullcourse. For example, using embodiments of the invention, a single doseor a few doses of the agent methotrexate may be administered to asubject having arthritis and in need of a therapeutic agent. If the geneexpression profile data set of the subject in response to the shortcourse of methotrexate correlates with data sets from subjects havingadverse reactions to this agent, then administration of a full course ofmethotrexate is counterindicated. Conversely, if the gene expressionprofile data set correlates with those of subjects who have respondedpositively to administration of a course of methotrexate treatment, thenthis therapeutic agent can be administered to the subject with muchlower probability of adverse reaction.

[0167] Discussion of Figures

[0168]FIGS. 1-4 illustrate some of the applications of calibratedprofile data sets. In FIG. 1, three possible scenarios are provided.Firstly, a candidate therapeutic agent may be tested to determine itsmolecular pharmacology and toxicology profiles. The test might includeobtaining calibrated profile data sets for a series of selected panelsselected on the basis of what activity is predicted for the drug. Thepopulation of cells exposed to the agent may be the result of in vivoadministration as depicted by the mouse or direct exposure in vitrowhere the cells may be an indicator cell line or an ex vivo sample fromthe subject. The result of the screen is the identification of moreeffective drug candidates for testing in human subjects.

[0169] The second scenario in FIG. 1 is the use of calibrated profiledata sets to identify a suitable clinical population for screening apotential therapeutic agent. Both demonstration of lack of toxicity anddemonstration of clinical efficacy require certain assumptions about theclinical population. The calibrated profile data sets provide a meansfor establishing those assumptions with respect to the biologicalcondition of the individuals selected for the clinical trials.

[0170] The third scenario in FIG. 1 involves the practice ofindividualized medicine, which may include creating an archive ofcalibrate profile data sets on the individual in a state of health suchthat changes can be identified using signature panels so as to permitevaluation, prognosis, or diagnosis of a particular condition. Moreover,stored information about the patient in the form of calibrated profiledata sets permits selecting one of a group of possible therapeuticagents most likely to be effective for the patient, optimizing dosage ofdrug, and detecting adverse effects that might arise through drug-druginteractions before symptoms arise. Use of calibrated profile data setsmay provide more efficient and cost-effective health care management.

[0171] The novel approach described above for evaluating a biologicalcondition of a subject may be applied to an ex vivo or in vitro assayfor measuring the effect of an agent on a biological condition asillustrated in FIGS. 2-4. A sample from the patient may measureddirectly ex vivo or tested ex vivo against an agent to predict an effectin the patient. This provides a quick and effective way to determinewhich drug, chosen from within a single class of drugs that all may beused to treat a particular condition, may be most effective for a givensubject. Alternatively, an agent may be tested on an indicator cell linethat can provide a quantitative measure of therapeutic performance in aclass of individuals.

[0172]FIG. 2 illustrates how calibrated profile data sets may assist inscreening a library of candidate compounds to discover candidate drugs.Starting with for example, 500 candidate drugs, these can be tested inindicator cells or ex vivo body fluid or tissues against signaturepanels for in vitro toxicology or metabolic indicators. The figureillustrates the large number of compounds that entered in late stages inthe development process only to ultimately be rejected due to adversebiological interactions. Use of calibrated profile data sets may in manyinstances more readily identify likely successful candidates and therebyreduce the expense and untoward effects of animal and humanexperimentation for compounds that could have been predicted to fail.

[0173]FIG. 3 illustrates how a compound may be administered to anexperimental animal such as a mouse or to an indicator cell line. The invivo or ex vivo or indicator cell sample may further be treated with astimulus. The result of both the compound and the stimulus may then bedetected, for example, using signature profiles for toxicity or formechanism to compare the effect of no drug+/−stimulus or +/−drug and nostimulus. Both in vitro (left panel of FIG. 3) and in vivo (right panelof FIG. 3) studies can be used to evaluate the effect of a compound(drug, nutraceutical, environmental stimuli, etc.). The right hand panelalso illustrates the specific embodiment of an “in vitro clinicaltrial”, that is, treatment of cells obtained from a subject and treatedwith a compound (with or without a stimulus) in vitro (or ex vivo) inorder to predict the outcome of similar treatment of the subject in vivo(see FIG. 15 for a specific example). The output from both panels isdescribed as toxicity and mechanistic profiles. Either experimentalcourse may be used to both evaluate potential toxicity, e.g., using thetoxicity, or liver metabolism selected panels, and to determine orconfirm likely mechanism of action by a critical selection of a genepanel(s) that illustrates and differentiates molecular mechanisms ofaction (see FIG. 12 for a specific example). These are merely examples,and other selected panels may be employed to evaluate or characterizeother biological effects or conditions. FIG. 4 illustrates a bioassay inwhich cells are removed from the subject and tested ex vivo with theaddition of a compound and also a challenge or stimulus. The ex vivoeffect of stimulus and then drug on whole blood taken from a humansubject is shown in FIG. 12 in which the stimulus is lipopolysaccharide(an inflammatory agent) while the drug is any of methotrexate,meclofenamate or methylprednisolone using a signature panel forinflammation. Methylprednisolone, a drug commonly used in the treatmentof acute exacerbations of COPD as well as in the chronic management ofthis disease, is considered to be a potent by non-specificanti-inflammatory agent. However, as demonstrated in FIG. 22, itseffects on gene expression are dependent on the stimulus. While thereare general qualitative similarities between the effects on geneexpression across these three stimuli, there are both quantitative andqualitative differences that may be important in understanding whenglucocorticoid intervention is warranted.

[0174] According to embodiments of the invention, an indicator cellpopulation is used to measure quantitative gene expression the effect ofan agent or a biological sample may influence the choice of whichindicator cell line will be most informative. For example, a cloned cellline such as THP-1 or a primary cell population (peripheral mononuclearcells) may provide information that is comparable to that obtained froma body sample directly (see FIG. 15). The normal state of geneexpression may range from zero or few transcripts to 10⁵ or moretranscripts.

[0175] Similarly, an agent may be evaluated for its effect on anypopulation of cells, either in vivo, ex vivo or in vitro, byadministering the agent and then determining a calibrate profile dataset for those cells under the selected conditions. Examples of thisapproach are provided in FIGS. 10-16 and 18. FIG. 18 further providescalibrated profile data sets for different concentrations of a singleagent showing that the transcription of selected constituents vary withdose and therefore the anticipated effectiveness with respect to thebiological condition.

[0176] The above description of determining a biological condition isexemplified as follows: the action of a pharmaceutical or nutraceuticalis measured with respect to its anti-inflammatory properties. Themeasurement of the effect may be established using a selected panel ofconstituent gene loci for example, an inflammation selected panel,including, Interleukin 1 alpha (IL-1α) or Tumor Necrosis Factor alpha(TNF-α). The anti-inflammatory effect may first be established bytreating indicator cells or sample cells ex vivo with a knowninflammation inducers (for example, lipopolysaccharide or othermitogens) followed by treatment with the experimental agent or conditionexpected to affect the expression from the appropriate gene loci.Accordingly, a baseline profile data set may be established in this caseas the gene expression for a particular panel of constituents resultingin the presence of the inflammation inducer. The addition of a potentialanti-inflammatory agent results in a change relative to the baseline.This approach is illustrated for example in FIG. 12. Methylprednisolonehas a substantial down regulation effect on IL-2 in blood cellsstimulated ex vivo with LPS where the baseline data set is LPSstimulated cells. In this case the effect is shown as negative. Incontrast, as shown in FIG. 16b, IL-2 appears to be upregulated in wholeblood not previously exposed to LPS, where the baseline data set isunstimulated cells. These results are consistent with the observationthat methylprednisolone stimulates IL-2 production.

[0177] The determination of the biological condition of a subject mayinclude measuring and storing additional data about the subject. Forexample, if the subject is a human or mammalian patient, additionalclinical indicators may be determined from blood chemistry, urinalysis,X-ray, other chemical assays and physical or sociological findings.

[0178]FIG. 7 illustrates how the accumulation of calibrated profile datasets may improve the predictive power of the database and therebyincrease its value in generating information about a biologicalcondition or agent. The figure indicates the use of the database interms of its power, for example, to predict the course of a therapeuticintervention or follow the course of an individual subject compared to apopulation. Information from the database may be used to predict alikely mechanism of metabolism or molecular mechanism of action, and tocompare a single profile to a collection of signature, calibratedselected profiles.

[0179] Use of a database in accordance with an embodiment of the presentinvention is illustrated in FIG. 8. FIG. 8 illustrates a data profileset from the database. Entries for input include a name, an ExperimentalType, and whether the entry is a New Reference; Cell/Tissue/Species andwhether these are new; Therapeutic agent (compound), Dose, andadditional parameters and whether the therapeutic agent is new.Observations are recorded according to the identity of a Gene (New Gene)and a Protein (New Protein). The Stimulus or other Treatment, if any,and the Dose are entered. Gene (and/or Protein) Expression, ExpressionValue, Expression Units if appropriate and Expression Time are shown.The figure specifically illustrates the range of applicable fields ofinvestigation from complex natural products to clinical trails inhumans, linkage to traditional forms of measurement and evaluation suchas literature citations, clinical indicators and traditionalpharmacokinetic measurements. Expert analysis of the selected profiledata contained in the database may then be used to guide productdevelopment and marketing, or used to improve the clinical decisionmaking concerning the health of a single individual or population ofindividuals.

[0180] One form of record may provide information about a subject oragent with respect to identity, medical history including traditionalpharmaceutical/medical data, clinical indications as determined fromliterature data, reference to additional types of analysis in thedatabase, etc.

[0181]FIG. 9 shows an embodiment of the present invention in whichprofile data is evaluated using data from a database that is remotelyaccessed over a network. Using the approach of this figure data may bederived at one or more locations (such as location 1 shown here),compared using information retrieved over communication path 1109 from acentral database at location 2, and the result of the comparison may beused to affect, for example, the course of treatment of an individual orpopulation. The communication path 1109 between location 1 and location2 is two-way, so that information resulting from determinations made atlocation 1 may delivered over the path 1109 to update the database 1108.The consequence is an iterative process whereby the information fromdatabase is used in a determination that may affect the course oftreatment, evaluation, or development, and the results of thedetermination become part of the database. In a first location, as inFIG. 5, from a tissue sample procured in process 1101, there are derivedmultiple RNA species pursuant to process 1102, and then in process 1103,profile data are quantified to produce a profile data set that ispertinent to the tissue sample obtained in process 1101. In order toevaluate the profile data set, in process 1104 information is retrievedfrom database 1108, which is located in a second location. In fact thedatabase may be in communication with a large number of locations, eachof which is generating profile data that must be evaluated. Theretrieval of information from the database is accomplished over acommunication path 1109, which may include a network such as theInternet, in a manner known in the art. Once information has beenobtained from the database 1108, the information is used in evaluatingthe quantified profile data in process 1105, with the result in process1106 that the medical condition of the subject may be assessed. Inprocess 1107, the database 1108 is updated over the communication path1109 to reflect the profile data that have been quantified in process1103. In this manner the database 1108 may be updated to reflect theprofile data obtained over all locations, and each location has thebenefit of the data obtained from all of the locations. While, forsimplicity, all of the processes in FIG. 9 are shown as taking place atlocation 1, some or even all of the processes may be implementedelsewhere, for example location 2, or in multiple locations. At location2, associated with the database, for example, may be a server that isused for hosting these processes, including evaluation of the quantifiedprofile data.

EXAMPLES Example 1

[0182] (a) Use of Whole Blood for Ex Vivo Assessment of a BiologicalCondition Affected by an Agent.

[0183] Human blood is obtained by venipuncture and prepared for assay byaliquotting samples for baseline, no stimulus, and stimulus withsufficient volume for at least three time points. Typical stimuliinclude lipopolysaccharide (LPS), phytohemagglutinin (PHA) andheat-killed staphylococci (HKS) or carrageenan and may be usedindividually (typically) or in combination. The aliquots of heparinized,whole blood are mixed without stimulus and held at 37° C. in anatmosphere of 5% CO2 for 30 minutes. Stimulus is added at varyingconcentrations, mixed and held loosely capped at 37° C. for 30 min.Additional test compounds may be added at this point and held forvarying times depending on the expected pharmacokinetics of the testcompound. At defined times, cells are collected by centrifugation, theplasma removed and RNA extracted by various standard means.

[0184] Nucleic acids, RNA and or DNA are purified from cells, tissues orfluids of the test population or indicator cell lines. RNA ispreferentially obtained from the nucleic acid mix using a variety ofstandard procedures (or RNA Isolation Strategies, pp. 55-104, in RNAMethodologies, A laboratory guide for isolation and characterization,2nd edition, 1998, Robert E. Farrell, Jr., Ed., Academic Press); in thepresent use using a filter-based RNA isolation system from Ambion(RNAqueous™, Phenol-free Total RNA Isolation Kit, Catalog #1912, version9908; Austin, Tex.).

[0185] In accordance with one procedure, the whole blood assay forselected profiles determination was carried out as follows: Human wholeblood was drawn into 10 mL Vacutainer tubes with Sodium Heparin. Bloodsamples were mixed by gently inverting tubes 4-5 times. The blood wasused within 10-15 minutes of draw. In the experiments, blood was diluted2-fold, i.e. per sample per time point, 0.6 mL whole blood+0.6 mLstimulus. The assay medium was prepared and the stimulus added asappropriate.

[0186] A quantity (0.6 mL) of whole blood was then added into each 12×75mm polypropylene tube. 0.6 mL of 2×LPS (from E. coli serotye 0127:B8,Sigma#L3880 or serotype 055, Sigma #L4005, 10 ng/ml, subject to changein different lots) into LPS tubes was added. Next, 0.6 mL assay mediumwas added to the “control” tubes with duplicate tubes for eachcondition. The caps were closed tightly. The tubes were inverted 2-3times to mix samples. Caps were loosened to first stop and the tubesincubated @ 37° C., 5% CO2 for 6 hours. At 6 hours, samples were gentlymixed to resuspend blood cells, and 1 mL was removed from each tube(using a micropipettor with barrier tip), and transferred to a 2 mL“dolphin” microfuge tube (Costar #3213).

[0187] The samples were then centrifuged for 5 min at 500×g, ambienttemperature (EC centrifuge or equivalent, in microfuge tube adapters inswinging bucket), and as much serum from each tube was removed aspossible and discarded. Cell pellets were placed on ice; and RNAextracted as soon as possible using an Ambion RNAqueous kit

[0188] (b) Amplification strategies.

[0189] Specific RNAs are amplified using message specific primers orrandom primers. The specific primers are synthesized from data obtainedfrom public databases (e.g., Unigene, National Center for BiotechnologyInformation, National Library of Medicine, Bethesda, Md.), includinginformation from genomic and cDNA libraries obtained from humans andother animals. Primers are chosen to preferentially amplify fromspecific RNAs obtained from the test or indicator samples, see, forexample, RT PCR, Chapter 15 in RNA Methodologies, A laboratory guide forisolation and characterization, 2nd edition, 1998, Robert E. Farrell,Jr., Ed., Academic Press; or Chapter 22 pp.143-151, RNA isolation andcharacterization protocols, Methods in molecular biology, Volume 86,1998, R. Rapley and D. L. Manning Eds., Human Press, or 14 inStatistical refinement of primer design parameters, Chapter 5, pp.55-72,PCR applications: protocols for functional genomics, M. A. Innis, D. H.Gelfand and J. J. Sninsky, Eds., 1999, Academic Press). Amplificationsare carried out in either isothermic conditions or using a thermalcycler (for example, a ABI 9600 or 9700 or 7700 obtained from AppliedBiosystems, Foster City, Calif.; see Nucleic acid detection methods, pp.1-24, in Molecular methods for virus detection, D. L. Wiedbrauk and D.H., Farkas, Eds., 1995, Academic Press). Amplified nucleic acids aredetected using fluorescent-tagged detection primers (see, for example,Taqman™ PCR Reagent Kit, Protocol, part number 402823 revision A, 1996,Applied Biosystems, Foster City Calif.) that are identified andsynthesized from publicly known databases as described for theamplification primers. In the present case, amplified DNA is detectedand quantified using the ABI Prism 7700 Sequence Detection Systemobtained from Applied Biosystems (Foster City, Calif.). Amounts ofspecific RNAs contained in the test-sample or obtained from theindicator cell lines can be related to the relative quantity offluorescence observed (see for example, Advances in quantitative PCRtechnology: 5′ nuclease assays, Y. S. Lie and C. J. Petropolus, CurrentOpinion in Biotechnology, 1998, 9:43-48, or Rapid thermal cycling andPCR kinetics, pp. 211-229, chapter 14 in PCR applications: protocols forfunctional genomics, M. A. Innis, D. H. Gelfand and J. J. Sninsky, Eds.,1999, Academic Press.

[0190] As a particular implementation of the approach described here, wedescribe in detail a procedure for synthesis of first strand cDNA foruse in PCR. This procedure can be used for both whole blood RNA and RNAextracted from cultured cells (i.e. THP-1 cells).

[0191] Materials

[0192] (1) Applied Biosystems TAQMAN Reverse Transcription Reagents Kit(P/N 808-0234). Kit Components: 10× TaqMan RT Buffer, 25 mM Magnesiumchloride, deoxyNTPs mixture, Random Hexamers, RNase Inhibitor,MultiScribe Reverse Transcriptase (50 U/mL) (2) RNase/DNase free water(DEPC Treated Water from Ambion (P/N 9915G), or equivalent)

[0193] Methods

[0194] 1 Place RNase Inhibitor and MultiScribe Reverse Transcriptase onice immediately. All other reagents can be thawed at room temperatureand then placed on ice.

[0195] 2 Remove RNA samples from −80° C. freezer and thaw at roomtemperature and then place immediately on ice.

[0196] 3 Prepare the following cocktail of Reverse TranscriptaseReagents for each 100 μL RT reaction (for multiple samples, prepareextra cocktail to allow for pipetting error):

[0197] 1 reaction (μL) 11×, e.g. 10 samples (μL) 11×, e.g. 1reaction(μL) 10 samples(μL) 10× RT Buffer 10.0 110.0 25 mM MgCl2 22.0242.0 dNTPs 20.0 220.0 Random Hexamers 5.0 55.0 RNAse Inhibitor 2.0 22.0Reverse Transcriptase 2.5 27.5 Water 18.5 203.5 Total: 80.0 880.0 (80 μLper sample)

[0198] 4 Bring each RNA sample to a total volume of 20 μL in a 1.5 mLmicrocentrifuge tube (for example, for THP-1 RNA, remove 10 μL RNA anddilute to 20 μL with RNase/DNase free water . . . for whole blood RNAuse 20 μL total RNA) and add 80 μL RT reaction mix from step 5.2.3. Mixby pipetting up and down.

[0199] 5 Incubate sample at room temperature for 10 minutes.

[0200] 6 Incubate sample at 37° C. for 1 hour.

[0201] 7 Incubate sample at 90° C. for 10 minutes.

[0202] 8 Quick spin samples in microcentrifuge.

[0203] 9 Place sample on ice if doing PCR immediately, otherwise storesample at −20° C. for future use.

[0204] 10 PCR QC should be run on all RT samples using 18S and β-actin(see SOP 200-020).

Example 2

[0205] Different inflammatory stimuli give rise to different, baselineprofile data sets so that the calibrated selected profiles for differentagents in the same class of anti-inflammatory result in differentsignature profiles.

[0206] FIGS. 11(a) and 11(b) show different inflammatory stimuli giverise to different, baseline profile data sets that may be used indetermining the calibrated selected profile data sets for the threeanti-inflammatory agents tested, and the resulting different signatureprofiles. The different profiles reflect the difference in the moleculartargets and mechanisms of action of the three agents derived from asingle class of therapeutics, anti-inflammatory agents. FIG. 11(a) alsoillustrate the extraordinary range of detection (y-axis) from less than10 fold difference from the calibrated profile with respect to someconstituents to a change of 10¹³ (10E13) in gene expression of oneconstituent (indeed the change for a constituent in FIG. 11(b) is 10⁻²²)when compared to the calibrator. Comparison to the calibrator results ingene expression profiles that are increased, decreased, or withoutchange from the calibrated set.

[0207]FIG. 11(a) shows relative gene expression (mRNA synthesis) inheat-killed staphylococci (HKS)-stimulated cells, and the effect ofthree different compounds (TPCK, UT-77, and “Dex”, or dexamethasone).Compound TPCK caused a 10-fold decrease in relative IFN-γ expression,and 100,000-fold decreases in IL-4 and IL-5 expression. Further,compound UT-77 caused even greater magnitude of increases in relativeexpression of the gene encoding IL-5, and more modest increases in IL-1expression (more than 10-fold) and IFN-γ. Such effects can be highlysignificant in disease etiologies and outcomes, and have predictivevalue concerning the usefulness as therapeutic agents of these compoundsor similar chemical entities or chemicals that act similarly. HKS cellsmay be used as an in vitro model of Gram-positive bacterial infection.

[0208]FIG. 11(b) displays analyses of expression of the 12 genes inlipopolysaccharide-(LPS)-treated cells, an in vitro model ofGram-negative bacterial infection. These data include several strikingcontrasts to the data in FIG. 11(a). Thus treatment with the therapeuticagent Dex caused a striking decrease in expression of the IL-2 gene inLPS-treated cells, and a striking increase in IL-2 expression inHKS-treated cells. Strikingly large differences in gene expression inthe differently stimulated cells can be seen for the IL-4 and the IL-5genes. Expression of the gene for IFN, in contrast, responded similarlyin cells treated by either of the stimuli and any of the therapeuticagents.

[0209] By these criteria, expression of the genes for IL-2, IL-4 andIL-5 were observed to be candidate markers or surrogate markers in cellmodel systems to distinguish responses of the cells to Gram-positive andGram-negative bacterial infection.

Example 3

[0210] A single therapeutic agent for treating a particular conditioncan be differentiated from a second therapeutic agent that also treatsthe particular condition by a signature profile for a given selectedpanel of gene loci.

[0211]FIG. 12 shows a calibrated profile data set for a panel having 8constituents that are indicative of a biological condition that includesinflammation. The profiles are shown for three differentanti-inflammatory agents-methotrexate, meclofenamate andmethylprednisolone. The calibrated profile data sets for each agent asshown represents a signature profile for that agent. This signatureprofile may serve as a device for establishing quality control for abatch of the agent. Indeed, it is envisaged that compounds or classes ofcompounds on the market or in development may be characterized by asignature profile. The signature profile may be represented in agraphical format, more particularly as a bar graph as provided in FIG.12. For FIG. 12, an ex vivo sample was tested. A sample of blood wastaken from the subject. Aliquots of the sample were subjected tolipopolysaccharide (LPS) ex vivo. After 30 minutes, theanti-inflammatory agent as indicated was added to an aliquot of thesample of blood and after about another 4 hours, the expression of thepanel of genes (Il-1α, Il-2, Il-8, Il-10, Il-12p35, Il-12p40, IL-15,IFN-Gamma and TNF-α) was determined. Although the calibrated profile ofmethotrexate and meclofenamate were similar, the calibrated profile ofmethylprednisolone was substantially different. Differences may bereflective of the differences of the mechanisms or target(s) of actionof this agent within the general class of anti-inflammatory compounds.The baseline is the profile data set for lipopolysaccharide absent anyadditional agents.

Example 4

[0212] There is relatively low variability with respect to the profilewithin a single individual over time when the calibrated selectedprofile is determined from the measurement of gene expression acrossmany gene loci that have been appropriately induced.

[0213] FIGS. 13(a), 13(b), and 13(c) show graphical representations ofcalibrated selected profile data sets for two different samples of wholeblood. Heparinized whole blood from a single normal healthy volunteerwas collected on two separate occasions of more than 2 weeks apart. FIG.13a, for sample 991116, and FIG. 13b, for sample 991028, reflect thebiological condition of the tested cells from the single donor using aselected panel (i.e., the inflammation selected panel) of 24 members, inresponse to stimulation with one of three different agents. The baselinein this example is derived from untreated cells obtained from the sameindividual. The calibrated profiles are shown for cells exposed for 4 to6 hours to lipopolysaccharide (LPS), heat-killed Stapylococci (HKS), andphytohemagglutinin (PHA). FIG. 13c shows a direct comparison ofLPS-stimulated blood sample 99116 with respect to blood sample 991028,i.e., 991028 is used as the calibrator or baseline profile data set. Themessenger RNA levels measured on Oct. 28, 1999 were used to compare thelevels of messenger RNA measured on Nov. 16, 1999. A perfect identity ofRNA levels would be represented by a flat line at unity. These data showthat for baseline gene expression, there can be as much as an 8 folddifference (c-jun) in messenger RNA levels. However, for most of thegenes measured, when there is no known substantial physiological changein the subject, the levels of messenger RNA measured on one day aresimilar to those measured on a different day. Changes in geneexpression, whether mRNA or protein, in excess of 10-20% may bereflective of biological changes in the subject even though traditionalclinical measurements may not identify such changes. FIG. 13(d) issimilar to FIG. 13(c) except that the cells were not stimulated withLPS.

[0214] FIGS. 13(a) through 13(d) document the relatively low variabilitywith respect to the profile within a single individual over time insimilar physiological conditions when the calibrated selected profile isdetermined from the measurement of gene expression across many gene locithat have been appropriately induced. The figures illustrate (1) theclass-specific effects (generally inflammatory as determined by theeffect on pro-inflammatory gene loci, e.g. TNF-alpha, IL-1 alpha andIL-1 beta), (2) the agent-specific effects quantitative differencesbetween each of the agents at the same gene loci (e.g., IL-2) and (3)reproducible and therefore predictable effects on the subjectpopulation, TK (FIG. 13c).

Example 5 Similarities and Differences in the Effect of a Single Agenton Cell Populations Differing in their Biological Condition

[0215] Ex-vivo gene expression analysis can be performed by obtainingthe blood of a subject for example by drawing the blood into avacutainer tube with sodium heparin as an anticoagulant. Ananti-inflammatory such as 3-methyl-prednisolone at a final concentrationof 10 micromolar was added to blood in a polypropylene tube, incubatedfor 30 minutes at 37 C in 5% CO₂. After 30 minutes a stimuli such as LPSat 10 ng/mL or heat killed staphlococcus (HKS) at 1:100 dilution wasadded to the drug treated whole blood. Incubation continued at 37° C. in5% CO₂ for 6 hours unless otherwise indicated. Erythrocytes were lysedin RBC lysis solution (Ambion) and remaining cells were lysed accordingto the Ambion RNAqueous-Blood module (catalog # 1913). RNA was eluted inAmbion elution solution. RNA was DNAsed treated with 1 unit of DNAse I(Ambion #2222) in 1× DNAse buffer at 37° C. for 30 minutes. In thisexample, first strand synthesis was performed using the AppliedBiosystems TaqMan Reverse Transcriptase kit with MultiScribe reversetranscriptase (catalog # N808-0234). Quality check of RT reactions wereperformed with Taqman PCR chemistry using the 18S rRNA pre-developedassay reagents (PDAR) from Applied Biosystems (part #4310893E). PCRassay of Source Selected Profiles were performed on 6 to 24 genes infour replicates on the Applied Biosystems 7700. PCR assays wereperformed according to specifications outlined with the PDAR product.Relative quantitation of the gene of interest was calibrated against 18SrRNA expression as described in Applied Biosystems product User Bulletin2 (1997) and elaborated in Hirayama, et al (Blood 92, 1998:46-52) using18S instead of GAPDH.

[0216] Relative quantitation of the mRNA was measured by the differencein threshold cycles between 18S and the gene of interest. This deltaC_(T) was then compared to the normalizing condition, either subjectbefore treatment, or stimuli without drug in an ex-vivo assay to measure“fold induction” represented in the bar graphs (FIG. 14). For example,in the above graph, IFN-levels are {fraction (1/50)} less on day 3 thanbefore treatment.

Example 6 In Vivo and Ex Vivo Samples Provide Comparable SignatureProfiles

[0217]FIG. 15 shows the calibrated profile data set for two subjects(Subject 1 and Subject 2) who have been treated over a three day periodwith a standard dose of the corticosteroids, dexamethasone. Blood fromeach subjects was obtained 72 hours later and a quantitative measure ofthe amount of RNA corresponding to the panel constituents wasdetermined. Although, the calibrated profile data set for each subjectwas similar for most gene loci, some notable differences were alsodetected, for example for Il-2, Il-10, Il-6 and GM-CSF. A calibratedprofile data set is also shown for comparison for an ex vivo sample ofblood from sample 1 prior to treatment with corticosteroid where the exvivo sample is subjected to an equivalent amount of corticosteroid invitro as calculated to be the plasma level in the subject. Thesimilarity in the calibrated profile data set for ex vivo samples whencompared to in vivo samples provides support for an in vitro assay thatwill predict the in vivo action of the compound. We have observed asimilar comparable effect between in vivo and ex vivo samples infectedwith an infectious agent, more particularly bacterial or viral agents.We have concluded therefore that the ex vivo samples provide aneffective method of determining the effect of a single compound ormultiple compounds on a patient, where the multiple compounds may beeither used in combination, in parallel or sequentially to optimize theselection of an agent for a biological condition for the subject.

Example 7 Demonstration of Reproducibility of an In Vitro Response withan Approved Anti-Inflammatory on 5 Different Donor Subjects

[0218] Comparison and analysis of the FIGS. 18a through 18 e demonstratethe consistency of effect of the stimulus and in vitro treatment with anapproved anti-inflammatory on 5 different donors (each figurerepresenting a unique donor). The use of a known and tested stimulusresults in a highly reproducible gene response in vitro that may becorrelated with a predictable in vivo response.

[0219]FIGS. 18a-18 e provide the results of analysis of 5 donors fromwhich a blood sample has been taken. The blood samples were exposed to atherapeutic agent at various concentrations ranging from 0.1 μM to 5 μM,more particularly 0.1 μM, 0.3 μM, 1 μM, 3 μM and 5 μM, for a 4 hourperiod. Different concentrations of the drug resulted in a calibratedprofile data set for an inflammation panel at each concentration thatwas qualitatively different from the next. FIG. 18a corresponds to donor1, FIG. 18b corresponds to donor 2, FIG. 18c corresponds to donor 3,FIG. 18d corresponds to donor 4, and FIG. 18e corresponds to donor 5.Each individual varied from the other and also provided a variableprofile for a different concentration. This set of figures illustratesthe high level of information obtainable by calibrated profile datasets.

Example 8

[0220] A calibrated profile data set may provide a signature profile fora complex mixture of compounds.

[0221]FIG. 21 illustrates the effect of three differentanti-inflammatory herbs on a selected panel of constituents includingconstituents of an Inflammation Selected Panel (TNF-α, Il-1b, ICAM,Il-8, Il-10, Il-12p40, ICE, cox-2, cox-1 and mmp-3) a cell growth anddifferentiation selected panel (c-fos, c-jun and STAT3), a toxicityselected panel (SOD-1, TACE, GR, HSP70, GST, c-fos, c-jun, INOS) and aliver metabolism selected panel (INOS, cyp-a and u-pa). The cellsassayed in FIG. 21 are aliquots of blood from a subject that are exposedex vivo to lipopolysaccharide and to Echinacea (SPM9910214) Arnica(SPM9910076) and Siberian Ginseng (SPM9910074), each of thenutraceuticals being applied to the blood sample at the sameconcentration of 200 ug/mL. The baseline is cell sample withlipopolysaccharide in the absence of a nutraceutical. Each nutraceutical(formed from a complex mixture) has a characteristic signature profilejust as did the single compound pharmaceutical anti-inflammatory agents.The signature profile may be provided in a graphic form that can be useto identify a herbal while providing information concerning itsproperties and its efficacy for a single subject or for an averagepopulation of subjects.

Example 9 A Quality Control Assay for Echinacea Brands Using CalibratedProfile Data Sets

[0222]FIG. 24 shows a graphic representation of the calibrated profiledata sets for four different commercial brands of Echinacea. Brandsusing an Inflammation Selected Panel. As expected, SPM007 and SPM003gave the signature, calibrated profiles similar to authentic Echinacea.Samples SPM010 and SPM 016, although labeled and sold as Echinacea whentested using the system described in FIG. 14, resulted in signaturecalibrated profiles that were substantially similar to the profileobtained with lipopolysaccharide alone. Echinacea samples SPM010 andSPM016 were found to have elevated, highly biologically active levels ofendotoxin while the LPS levels in SP007 and SP003 were undetectable. Astored signature profile for active Echinacea obtained from a selectedpanel designed to test efficacy and mode of action, e.g., theinflammation panel, permits evaluation of new batches of Echinacea,differentiation of existing or new brands of Echinacea, guide theisolation and development of new compounds with different or similaractivities from a complex compound like Echinacea or may be used in thedevelopment of quality assurance in the production, analysis and sale ofnew or previously marketed compounds. In the example cited, two of thebrands of Echinacea SP010 and SP016 result in calibrated profiles thatare characteristic of authentic Echinacea.

Example 10 Comparison of Three Herbal Preparations Using an IndicatorCell Line

[0223] FIGS. 25(a) through 25(c) provide calibrated profile data setsfor three herbal preparations with respect to an indicator cell line(THP-1) rather than a blood sample from a subject. In FIG. 25(a), thebaseline is the profile data set for THP-1 cells absent the herbal whilethe histograms represent the calibrated profile data sets for the sameherbal from three different manufacturing sources of the same herb at250 ug/ml. Gene expression results are shown on a log scale. Similar tothe observation in FIG. 14, these demonstrate that similarly labeledcompounds obtained from different sources have demonstrable andquantifiable differences in calibrated profiles using a specific panel,e.g., the inflammation selected panel designed to obtain informationabout the expression of gene products related to inflammation andinfection. This suggests that the compounds likely have differentefficacies when used for specific purposes.

[0224]FIG. 25(b) provides a comparison of the calibrated profile of asingle herb at three concentrations using the indicator cell line ofTHP-1. The baseline profile data set is untreated THP-1 cells. Analysisof the data suggests a concentration-dependent response in the indicatorcell lines which, although demonstrated here, may be indicative of asimilar response in subjects.

[0225]FIG. 25(c) provides a comparison of four commercial Echinaceabrands used at the same concentration and tested against a panel ofconstituents using a THP-1 cell line as an indicator cell population.Differential expression, as revealed, for example, by inspection orcalculation of differences in the calibrated profiles, allows directcomparisons of complex compounds to be made. For example, analysis ofthe differences in the calibrated profiles may be used to guide compoundisolation and development, product differentiation in the marketplace,or used by the consumer or health professional to guide theindividualized choice of a single compound from a class of similarcompounds that may be suited for a particular biological condition.

Example 11 Set Up of a 24-Gene Human Selected Panel for Inflammation

[0226] Materials 1 20× Primer/Probe Mix for each gene of interest. 2 20×Primer/Probe Mix for 18S endogenous control. 3 2× Taqman Universal PCRMaster Mix 4 cDNA transcribed from RNA extracted from cells 5 AppliedBiosystems 96-Well Optical Reaction Plates 6 Applied Biosystems OpticalCaps, or optical-clear film 7 AB Prisma 7700 Sequence Detector

[0227] Methods

[0228] 1 Make stocks of each Primer/Probe mix containing thePrimer/Probe for the gene of interest, Primer/Probe for 18S endogenouscontrol, and 2×PCR Master Mix as follows. Make sufficient excess toallow for pipetting error e.g. approximately 10% excess. The followingexample illustrates a typical set up for one gene with quadruplicatesamples testing two conditions (2 plates). 9× 1×(1 well) (2 platesworth) 2× Master Mix 12.50 112.50 20× 18S Primer/Probe Mix 1.25 11.2520× Gene of interest 1.25 11.25 Primer/Probe Mix Total 15.00 135.00

[0229] 2 Make stocks of cDNA targets by diluting 95 μl of cDNA into 2000μl of water. The amount of cDNA to be adjusted to give Ct values between10 and 18.

[0230] 3 Pipette 15 μl of Primer/Probe mix into the appropriate wells ofa Applied Biosystem 96-Well Optical Reaction Plate.

[0231] 4 Pipette 10 μl of cDNA stock solution into each well of theApplies Biosystems 96-Well Optical Reaction Plate.

[0232] 5 Seal the plate with Applied Biosystems Optical Caps, oroptical-clear film.

[0233] 6 Analyze the plate on the AB Prism 7700 Sequence Detector.

[0234] In Examples 12 through 19 below, procedures analogous to those ofExamples 1 and 11 were followed to determine relative mRNA expression.

Example 12

[0235] Calibrated profile data sets, using a subset of the InflammationSelected Panel, show the effect of administration of a steroid.

[0236] In FIGS. 26(a) and 26(c), subjects 1 and 2 respectively have beensubjected to a course of administration of methylprednisone twice a dayfor three consecutive days. In FIGS. 26(b) and 26(d), two otherindividuals, identified as control 1 and control 2 respectively, wereadministered a placebo over a corresponding period. In each case, theblood samples of the individuals were taken prior to the course ofadministration and immediately following the course of administration.The graphs of these each of these figures show the relativeconcentration of each constituent of a subset of the InflammationSelected Panel, the subset being chosen for its ability to discriminateas to the effect of anti-inflammatory agents. For each constituent, thepost-administration concentration is shown as a ratio in relation to itspre-administration concentration; hence the baseline of 1 is indicativeof the same concentration of the constituent before and afteradministration, and the presence of a bar below the baseline indicates apost-administration drop in concentration of the constituent. FIGS.26(a) and 26(c) show that the response of subjects 1 and 2 to theadministration of the steroid are qualitatively and quantitativelysimilar—indeed, strikingly similar. Moreover, and in contrast, theresponses of controls 1 and 2 to the placebo are markedly distinct fromthe responses of subjects 1 and 2.

Example 13

[0237] Calibrated profile data sets, using a subset of the InflammationSelected Panel, provide a comparison of the effects of administration ofmethylprednisone and Ibuprofen. In this example, FIGS. 27(a) and 27(c)are identical to FIGS. 26(a) and 26(c), and show the responses ofsubjects 1 and 2 respectively to the administration of methylprednisone.FIGS. 27(b) and 27(d) show the responses of the same subjects, namelysubjects 1 and 2 respectively, to the administration of high-doseIbuprofen (800 mg administered three times per day over a three-dayperiod). (FIGS. 27(b) and 27(d) use the same conventions as FIGS. 27(a)and 27(c) in showing post-administration concentration of constituentsrelative to pre-administration concentration.) It can be seen from thesefigures that the responses of the subjects to Ibuprofen arequalitatively and quantitatively similar—again, strikingly similar.Moreover, the responses of the subjects to Ibuprofen are distinct fromthe responses of the subjects to methylprednisone. In fact, the distinctpattern of response to Ibuprofen correlates with other information knownabout Ibuprofen. For example, IL-1-β is known to be of importance inresponding to joint destruction, and Ibuprofen here is shown as notraising the level (and in the case of subject 2, lowering the level) ofIL-1-β expression. And Ibuprofen is known to be not very effective intreating joint destruction. Similarly, IL-10 activity is associated withanti-inflammatory activity and is useful in addressing bowelinflammatory disease; Ibuprofen here is shown as in fact depressing thelevel of IL-10 expression. These phenomena are consistent with the factthat Ibuprofen is known to be ineffective in addressing bowelinflammatory disease.

Example 14

[0238] Calibrated profile data sets, using a subset of the InflammationSelected Panel, identify chronic obstructive pulmonary disease (COPD)patients.

[0239] The graphs of these each of FIGS. 28(a) through 28(d) show therelative concentration of each constituent of a subset of theInflammation Selected Panel, the subset being chosen for its ability todiscriminate as to the presence of COPD. For each constituent, theconcentration is shown as a ratio in relation to a concentration that isnormative of the concentrations of the constituent in a population ofhealthy subjects. Thus for any constituent, a baseline level of 1corresponds to a normal concentration. FIGS. 28(a) and 28(c) show therelative concentrations of constituents in COPD patients 1 and 2respectively, while FIGS. 28(b) and 28(d) show the relativeconcentrations of constituents in two healthy individuals identified ascontrol 1 and control 2 respectively. Indeed, FIGS. 28(b) and 28(d) showlevels of constituents in controls 1 and 2 as being close to populationnormals, whereas FIGS. 28(a) and 28(c) show levels of constituents inCOPD patients 1 and 2 as being dramatically different from normallevels.

Example 15

[0240] Evaluations of the effects of drug exposure performed in vitrocorrespond closely with evaluations performed in vivo, employing in eachcase calibrated profile data sets, using a subset of the InflammationSelected Panel.

[0241] FIGS. 29(a) and 29(b) present graphs showing response to theadministration of methylprednisone. The response shows the relativeconcentration of each constituent of a subset of the InflammationSelected Panel, the subset being chosen for its ability to discriminateas to the effect of anti-inflammatory agents. For each constituentillustrated, the darker bar (on the right) shows the in vivo response ofa subject to a course of administration of methylprednisone twice a dayfor three consecutive days. In the in vivo cases, a blood sample of thesubject was taken prior to the course of administration and immediatelyfollowing the course of administration, the constituents were measured,and the responses are shown in FIGS. 29(a) and 29(b). Thepost-administration concentration of each constituent is shown as aratio in relation to its pre-administration concentration; hence thebaseline of 1 is indicative of the same concentrationpost-administration as pre-administration. The procedures of FIGS. 29(a)and 29(b) were conducted on two different occasions a year apart. At thesame time that each in vivo procedure was conducted, methylprednisonewas also administered in vitro to a sample of the blood of the samesubject. For each constituent illustrated in each of FIGS. 29(a) and29(b), the lighter bar (on the left) shows the in vitro response of thesample to the administration of the drug. Again, the post-administrationconcentration of each constituent is shown as a ratio in relation to itspre-administration concentration.

[0242] What is remarkable about the results shown in FIGS. 29(a) and29(b) is that in each procedure, the in vitro response is strikinglysimilar to the in vivo response, in most cases even where the results invivo differed over time. This result shows the value of in vitromodeling for the evaluation of the effect of the administration ofagents using Selected Panels.

Example 16

[0243] The effect of different agents is evaluated using a subset of theSelected Prostate Panel.

[0244] In FIG. 30 is shown the response of five different cell lines tothe administration of various agents, using a subset of the SelectedProstate Panel (listed in Table 5). This figure also shows broadfunctions of constituents of the panel.

Example 17

[0245] The use of a rat liver metabolism selected panel to measure theeffect of a pharmaceutical agent, clofibrate, Male rats were treatedwith 400 mg/kg/day of clofibrate administered by mouth and the levels ofgene expression were measured in liver tissue. Clofibrate is used herebecause its metabolism in the rat and human liver is well described. Asexpected, clofibrate induces gene expression at the cyp 1A1 locus, butthe agent also induces expression at a number of other metabolic loci inthe selected panel as measured in this cohort of in-bred Spraque-Dawleyrats. The ratio of the concentration of each constituent for theclofibrate treated rats is measured with reference to a control(baseline) which is a set of rats treated only with the carriercompound. The resultant selected profile is provided in FIG. 31.

Example 18 The Ability of the Rat Metabolism Selected Panel toDifferentiate Drug Responses

[0246] Male rats were treated with 400 mg/kg/day of clofibrate orbenzo[a]pyrene administered by mouth and the levels of gene expressionwere measured in liver tissue. The response to clofibrate andbenzo[a]pyrene was determined in Spraque-Dawley rats using a ratmetabolism panel. The results are shown in FIG. 32. Each drug gives acharacteristic and distinct pattern of gene induction across theselected panel. As expected from the prior art, benzo[a]pyrenespecifically induces gene expression at the loci for cyp 4A1 and HD. Thecontrol (baseline) is a set of rats treated only with the carriercontrol.

Example 19

[0247] The effect of administration of a stimulant is measured by askin-epithelial/vascular/inflammation selected panel.

[0248]FIG. 33 illustrates the response of a subject to theadministration of a stimulant (TNF-alpha, 10 ng/ml), as measured by askin-epithelial, vascular/inflammation selected panel. In this example,the selected panel is created from constituents that are also found inother panels which have been here selected for purposes of bestestablishing an effect resulting from the stimulant.

Example 20 Use of a Human Liver Selected Panel for Determining theMetabolic Properties of Cryopreserved Human Hepatocytes

[0249] Time/dose response experiments utilizing compounds withwell-described toxicities and mechanisms of action are an early step inthe biological validation of the selected panel. FIG. 34 shows the geneexpression profile resulting from a timed study at constant dose ofbenzo(a)pyrene when administered to cryopreserved human hepatocytes.

Example 21 Response of Human Umbilical Vein Endothelial Cells to TNF-α

[0250]FIG. 35 illustrates how endothelial cells respond to theinflammatory TNFα by the induction of expression of a number of geneloci, notably the adhesion molecules ELAM, ICAM, and VCAM. The cellswere exposed for 24 hours. Both 5 ng/ml and 10 ng/ml are high doses ofthe immunostimulant TNFα and, as expected, no clear concentrationresponse is observed at this dose level.

Example 22

[0251] This example is one illustration of the wide embodiments of theselected panels. In this example the effect of a compound in solution(NAC) is compared directly to the effect of an environmental stimulus(UVB) and the combined effect is read out as differential geneexpression. FIG. 19 illustrates an similar effect of NAC only in bloodobtained smokers and non-smokers. Dose and time experiments wereconducted prior to this illustrated experiment.

Example 23

[0252] Gene expression profiles provide information on the effect of anenvironmental stimulus on cells.

[0253] This example is one illustration of the wide embodiments of theselected panels. In this example (see FIG. 36) the effect of a compoundin solution (N-acetylcysteine) is compared directly to the effect of anenvironmental stimulus (UVB) and the combined effect is read out asdifferential gene expression. FIG. 19 illustrates an similar effect ofNAC only in blood obtained smokers and non-smokers. Dose and timeexperiments were conducted prior to this illustrated experiment. TABLE 1Inflammation Selected Panel IL-1α Interleukin-1 alpha IL-1βInterleukin-1Beta IL-2 Interleukin-2 IL-4 Interleukin-4 IL-6Interleukin-6 IL-7 Interleukin-7 IL-8 Interleukin-8 IL-10 Interleukin-10IL-12p40 Interleukin-12p40 IL-15 Interleukin-15 IL-18 Interleukin-18GM-CSF Granulocyte colony stimulating factor IFN-γ Interferon gammaTGF-α Tumor growth factor alpha TNF-α Tumor necrosis factor alpha TNF-βTumor necrosis factor beta Cox 2 Cyclooxygenase/prostaglandin-endoperoxide synthase 2 ICE Interleukin-1 converting enzyme c-jun MKK7,MAP2K7 mmp9 Matrix metalloproteinase UPA Urokinase plasminogen activatorHSP70 Heat Shock Protein 70 kDa CRE cAMP Response Element ICAMIntercellular Adhesion Molecule

[0254] TABLE 2 Cell Growth and Differentiation Selected Panel BIRC5(Survivin) Apoptosis Inhibitor NFKB1 NF-kappaB CDKN2A (P16) Cell cycleinhibitor TP53 (P53) Tumor suppressor TNF-α Tumor Necrosis Factor alphaTERT Telomerase Catalytic Subunit BCL2 Represses Apoptosis BAX PromotesApoptosis CASP1 (ICE) Interleukin Converting Enzyme GADD45A Growtharrest protein TNFRSF11A (RANK) Receptor activator of NFkB PDCD8 (AIF)Apoptosis Inducing Factor Apaf-1 Apoptotic protease activating factor 1DFFB (DFF40) Caspase activated DNAse BAIAP3 (IAP1, BIRC3) Inhibitor ofapoptosis protein 1 (BAI-associated protein 3) BIRC2 (IAP2) Inhibitor ofapoptosis protein 2 Bik BCL2 interacting killer BCL2L1 (BCL-X) BCL2-Like1 DAD1 Defender against cell death 1 MADD MAP Kinase activating deathdomain MAP3K14 Mitogen-activated protein kinase 3, 14 PTEN Proteintyrosine phosphatase k-alpha-1 Alpha tubulin (housekeeping, highabundance) TOSO Anti-fas induced apoptosis cdk2 Cyclin dependent kinase2 cdk4 Cyclin dependent kinase 4 CASP3 Apoptosis-related cysteineprotease, 3 CASP9 Apoptosis-related cysteine protease, 9 RAD52 DNA dsbreak repair XRCC5 (Ku80) X-ray repair complementing defective repair inChinese hamster cells 5 PNKP Polynucleotide kinase phosphatase MRE11AMeiotic recombination 11 homolog A CCND1 (cyclinD1) PRAD1: parathyroidadenomatosis 1 CCND3 (cyclin D3) Cyclin D3 CCNE1 (cyclin E) Cyclin ECCNA2 (cyclin A) Cyclin A CCNB1 (cyclin B) Cyclin B CDKN2B (p15)Cyclin-dependent kinase inhibitor 2B (p15, inhibits CDK4) CDKN1A (p21)Cyclin-dependent kinase inhibitor 1A (p21, Cip1) RB1 Retinoblastoma BIDBH3 interacting domain death agonist BAK1 BCL2-antagonist/killer 1 BADBCL2-antagonist of cell death SMAC Second mitochondria-derived activatorof caspase VDAC1 Voltage-dependent anion channel 1 CHEK1 Checkpoint, S.pombe, homolog of, 1 ABL1 v-abl Abelson murine leukemia viral oncogenehomolog 1 TNFRSF12 Tumor necrosis factor receptor superfamily, member 12TRADD TNFRSF1A-associated via death domain FADD Fas (TNFRSF6)-associatedvia death domain TRAF1 TNFR associated factor 1 TRAF2 TNFR associatedfactor 2

[0255] TABLE 3 Human Liver Metabolism and Toxicity Selected Panel (SeeFIG. 34) CYP1A2 Polycyclic aromatic hydrocarbon (PAH) metabolism;induced by smoking Catalyzes formation of toxic APAP metabolite CYP2A6Catalyzes oxidation in some Pharmaceuticals, procarcinogens, and smokeconstituents; upregulated in vitro after exposure to barbiturates ordex. CYP2E1 Converts many small organic Compounds (i.e. EtOH, APAP,CC14) into reactive intermediates. Induced in alcoholics and in fattyliver phenotype. CYP2D6 Broad catalytic activities for over 30therapeutic drugs. CYP3A4 Metabolism for a wide variety of drug typesUGT2B7 UDP glycosyltransferase 2B7 UGT2B15 UDP glycosyltransferase 2B15EPHX1 Microsomal epoxide hydrolase Multiple tissue-specific splicingvariants GSTA1 Glutathione S-transferase alpha 1 GSTA2 GlutathioneS-transferase alpha 2 UCP-2 Mitochondrial uncoupling protein 2 TNF-αLocal inflammation Endothelial activation Released by PBMCs, Kupffercells and activated tissue macrophages in the liver TGF-β Transforminggrowth factor beta 1 iNOS Inducible nitric oxide synthase; SCF Stem cellfactor, released by activated hepatic stellate cells (HSC*); recruitsmast cells (MC) to the liver IFN-γ Activation of macrophages Galectin-3β-galactoside-binding lectin associated with cell growth, tumortransformation, and metastasis. FAP Fibroblast activation protein;membrane protease expressed at sites of tissue remodeling. ProcollagenExtracellular matrix protein C-proteinase (bone morphogenetic protein 1)(aka BMP1) required for cartilage formation Collagen I Extracellularmatrix (ECM) component Collagen III ECM component Collagen IV ECMcomponent Laminin ECM component Fibronectin ECM component

[0256] TABLE 4 Skin Response Selected Panel CRABP2 Cellular retinoicacid-binding protein 2 KRT14 Keratin 14 KRT5 Keratin 5 KRT16 Keratin 16FGF7 Fibroblast growth factor (KGF) Keratinocyte growth factor FN1Fibronectin 1 IVL Involucrin COL7A1 Type VII collagen, alpha 1 CTGFConnective tissue growth factor IL-1α Interleukin-1α IL-8 Interleukin 8GRO1 Melanoma growth stimulatory activity (MGSA) PTGS2Prostaglandin-endoperoxide synthase 2 (COX2) Cyclooxygenase 2 TNF-αTumor necrosis factor alpha TGF-β1 Transforming growth factor beta 1 PI3Proteinase inhibitor 3 (SKALP) Skin-derived antileukoproteinase BSGBasignin (EMMPRIN) Extracellular MMP inducer MMP1 Matrixmetalloproteinase 1 (interstitial collagenase) MMP2 Matrixmetalloproteinase 2 (72 kD gelatinase) MMP3 Matrix Metalloproteinase 3(Stromelysin 1) TIMP1 Tissue inhibitor of matrix metalloproteinase HMOX1Heme oxygenase 1 GADD45A Growth arrest and DNA- damage-inducible alphaPCNA Proliferating cell nuclear antigen DUSP1 Dual specificityphosphatase(CL100) MAPK8 Mitogen activated protein kinase 8 TP53 Tumorprotein p53 (p53) Bcl2 B-cell CLL/lymphoma 2 Bax Bcl2-associated Xprotein JUN c-jun FOS c-fos NR1I2 Nuclear receptor subfamily 1, group I,member 2 (PAR2) Protease activated receptor 2 S100A7 S100calcium-binding protein A7 (PSOR1) psoriasin 1 TNSF6 Tumor necrosisfactor (ligand) superfamily, member 6 (FASL) Fas ligand

[0257] TABLE 5 Prostate Selected Panel (See FIG. 30) PSA ProstateSpecific Antigen DD3 Prostate cancer antigen 3 Survivin ApoptosisInhibitor 4 PSMA Prostate Specific Membrane Antigen Folate Hydrolase 1TERT Telomerase Reverse Transcriptase Telomerase Catalytic Subunit KLK2Human Kallikrein 2 PDEF Prostate-Derived Ets Factor PSCA Prostate StemCell Antigen POV1 Prostate Cancer Overexpressed Gene 1 PART-1 ProstateAndrogen-Regulated Transcript 1 MYC c-myc NRP1 Neurophilin 1 KAI1 HumanMetastasis Suppressor Gene LGALS8 Galectin 8 p16 Cyclin-Dependent Kinase2A GSTT1 Glutathione-S-Transferase theta 1 PAI1 Plasminogen ActivatorInhibitor 1 bcl-2 B-cell CLL/Lymphoma 2 STAT3 Transcriptional activatorIL-6 Interleukin 6 u-pa Urokinase-Type Plasminogen Activator KRT-5Keratin 5 TGF-β Transforming Growth Factor Beta IL-8 Interleukin 8 VEGFVascular Endothelia Growth Factor ACPP Acid phosphatase, prostate KRT-19Keratin 19 CK-8 Cytokeratin 8 Maspin Protease Inhibitor 5 HMG-I/YNon-histone chromosomal protein IGFR1 Insulin Growth Factor Receptor 1HUPAP Human Prostate-Associated Protease P53 Tumor suppressor COX-2Cyclooxygenase 2 E-CAD e-cadherin N-CAD n-cadherin CTNNA1 α-1 cateninPCANAP7 Prostate cancer associated gene 7 MRP1 Multiple Drug ResistanceProtein 1 HSP-70 Heat shock protein TNF-α Tumor Necrosis Factor

[0258] TABLE 6 Vascular Selected Panel VEGF Vascular Endothelial GrowthFactor NF kappa B Nuclear Factor kappa B TEK/TIE2 Tyrosine kinase,endothelial ERK2 MAPK1: mitogen-activated protein kinase 1 SELE selectinE (endothelial adhesion molecule 1) Flt-1 fms-related tyrosine kinase 1(vascular endothelial growth factor/vascular permeability factorreceptor) PTX3 pentaxin-related gene, rapidly induced by IL-1 betaHMOX-1 HMOX1 = heme oxygenase (decycling) 1 HIF-1 Hypoxia-induciblefactor 1, alpha subunit GRD1 Glutathione Reductase 1 iNOS Induciblenitric oxide synthase ET-1 Endothelin 1 ECE-1 endothelin convertingenzyme 1 PLAT plasminogen activator, tissue ADAMTS1 a disintegrin-likeand metalloprotease (reprolysin type) with thrombospondin type 1 motif,1 PTGIS prostaglandin I2 (prostacyclin) synthase COX-2prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase andcyclooxygenase) VCAM vascular cell adhesion molecule 1 IL-8 Interleukin8 II-1β Interleukin-1 beta IGFBP3 Insulin-like growth factor bindingprotein 3 GJA1 gap junction protein, alpha 1, 43 kD ICAM-1 intercellularadhesion molecule 1

[0259] TABLE 7 Rat Liver Metabolism and Toxicity Panel (See FIGS. 31 and32) 1 ALDH 2 aldose reductase 3 ARG 4 CYP1A1 5 CYP1B1 6 CYP2A2 7 CYP2B28 CYP2C11 9 CYP2D2 10 CYP2E1 11 CYP2A1 12 CYP3A1 13 CYP1A2 14 CYP4A1 15CYP4A3 16 CYP4F1 17 cytochrome P450 oxidoreductase 18 epoxide hydrolase19 HD 20 MAO-B 21 quinone reductase 22 alpha-1-AGP 23 PPAR-alpha 24 GGT

We claim:
 1. A kit of primer-probe combinations for measuring expressionproducts of at least four constituents selected from any one of Tables 1through
 7. 2. A kit according to claim 1, wherein each primer probecombination is constructed so as to hybridize only to at least one ofcDNA and mRNA at a biologically relevant locus.
 3. A kit according toclaim 1, wherein in each combination a reverse primer is complementaryto a coding DNA strand located across an intron-exon junction, with notmore than three bases of a three-prime end of the reverse primer beingcomplementary to a proximal exon.
 4. A method of using a kit accordingto any of claims 1-3 for analyzing a patient for a biological conditionat a remote site, comprising: a. providing a kit for measuring a profiledata base for evaluating a biological condition, the kit includingreagents for quantitative analysis of RNA for a panel of gene loci; b.accessing a centralized database containing baseline profile data setscorresponding to the panel; c. determining a calibrated profile data setfor the patient; and d. analyzing the biological condition of thepatient with respect to a library of calibrated profile data sets.
 5. Amethod of using a kit according to claim 4, wherein quantitativeanalysis of RNA comprises: quantitatively measuring the amount of adistinct RNA constituent in a panel of constituents selected so thatmeasurement enables evaluation of a biological condition of patient,based on a sample from the patient, the sample providing a source ofRNAs, wherein such measure for each constituent is obtained undermeasurement conditions that are substantially reproducible.
 6. A methodof using a kit according to claim 5, wherein the measurement conditionsthat are substantially repeatable are within a degree of repeatabilityof better than five percent. 7 A method of using a kit according toclaim 5, wherein the measurement conditions that are substantiallyrepeatable are within a degree of repeatability of better than threepercent.
 8. A method of using a kit according to claim 5, wherein themeasurement conditions that are reproducible include intra-assayvariability and inter-assay variability.
 9. A method of using a kitaccording to claim 8, wherein intra-assay variability is reproduciblesuch that the average coefficient of variation for measurements for eachassay is less than 1 percent.
 10. A method of using a kit according toclaim 8, wherein inter-assay variability is reproducible such that theaverage coefficient of variation for measurements for each value is lessthan 2 percent.